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Ecosystem-scale estimation of photosynthesis and respiration using micrometeorological techniques remains an important, yet difficult, challenge. In this study, we combined micrometeorological and stable isotope methods to partition net ecosystem CO2 exchange (FN) into photosynthesis (F(A)) and respiration (F(R)) in a corn-soybean rotation ecosystem during the summer 2003 corn phase. Mixing ratios of (12)CO2 and (13)CO2 were measured continuously using tunable diode laser (TDL) absorption spectroscopy. The dynamics of the isotope ratio of ecosystem respiration (R), net ecosystem CO2 exchange (deltaN) and photosynthetic discrimination at the canopy scale (delta canopy) were examined. During the period of full canopy closure, F(N) was partitioned into photosynthesis and respiration using both the isotopic approach and the conventional night-time-derived regression methodology. Results showed that deltaR had significant seasonal variation (-32 to -11% per hundred) corresponding closely with canopy phenology. Daytime deltaN typically varied from -12 to -4% per hundred, while delta canopy remained relatively constant in the vicinity of 3% per hundred. Compared with the regression approach, the isotopic flux partitioning showed more short-term variations and was considerably more symmetric about F(N). In this experiment, the isotopic partitioning resulted in larger uncertainties, most of which were caused by the uncertainties in deltaN. and the daytime estimate of deltaR. By sufficiently reducing these uncertainties, the tunable diode laser (TDL)-micrometeorological technique should yield a better understanding of the processes controlling photosynthesis, respiration and ecosystem-scale discrimination.

The effects of dams on carbon dioxide (CO2) fluxes in downstream lakes remain elusive. Here we combined eddy covariance observations and random forest models to examine multi‐decadal variations in CO2 fluxes in the Poyang Lake, the largest freshwater lake in China, and quantified the contribution of the Three Gorges Dam (TGD), the world's largest hydraulic project. We found the lake fluctuated between CO2 source and sink in 1961–2016, and tended to be CO2 sink in the post‐TGD period (2003–2016) when vegetation expanded early and spatially due to declining water level. TGD can explain approximately 6% of the total differences in annual CO2 fluxes, with major contributions in the impoundment period (up to 22% in middle September to October). The results show a positive side of operational major hydraulic projects on lake carbon sink, and probably caution the negative side of carbon release after dam removal. Plain Language Summary: In the past century, dams have significantly altered the hydrological connectivity between rivers and lakes, which affect CO2 exchange in the downstream lake systems. As the largest freshwater lake in China, Poyang Lake has also undergone drastic hydrological changes, attributable largely to the operation of the Three Gorges Dam (TGD), the world's largest hydraulic project ever, in 2003. Based on flux observations and machine learning method, we show that annual lake CO2 exchange shifted toward carbon sink during 1961–2016. The TGD has a major impact on lake CO2 fluxes, especially during the impoundment stage in middle September–October, explaining 22% of the flux differences between the pre‐ and post‐TGD period. The results show a positive side of hydraulic projects albeit their adverse impact on ecological protection. Key Points: Poyang Lake as a CO2 source or sink significantly depends on water levelPoyang Lake became a CO2 sink since the Three Gorges Dam operation in 2003Dam explains 22% of differences in CO2 fluxes in autumn impoundment period [ABSTRACT FROM AUTHOR]

The atmospheric carbon dioxide (CO 2) mixing ratio and its carbon isotope (δ13 C-CO 2) composition contain important CO 2 sink and source information spanning from ecosystem to global scales. The observation and simulation for both CO 2 and δ13 C-CO 2 can be used to constrain regional emissions and better understand the anthropogenic and natural mechanisms that control δ13 C-CO 2 variations. Such work remains rare for urban environments, especially megacities. Here, we used near-continuous CO 2 and δ13 C-CO 2 measurements, from September 2013 to August 2015, and inverse modeling to constrain the CO 2 budget and investigate the main factors that dominated δ13 C-CO 2 variations for the Yangtze River delta (YRD) region, one of the largest anthropogenic CO 2 hotspots and densely populated regions in China. We used the WRF-STILT model framework with category-specified EDGAR v4.3.2 CO 2 inventories to simulate hourly CO 2 mixing ratios and δ13 C-CO 2 , evaluated these simulations with observations, and constrained the total anthropogenic CO 2 emission. We show that (1) top-down and bottom-up estimates of anthropogenic CO 2 emissions agreed well (bias < 6 %) on an annual basis, (2) the WRF-STILT model can generally reproduce the observed diel and seasonal atmospheric δ13 C-CO 2 variations, and (3) anthropogenic CO 2 emissions played a much larger role than ecosystems in controlling the δ13 C-CO 2 seasonality. When excluding ecosystem respiration and photosynthetic discrimination in the YRD area, δ13 C-CO 2 seasonality increased from 1.53 ‰ to 1.66 ‰. (4) Atmospheric transport processes in summer amplified the cement CO 2 enhancement proportions in the YRD area, which dominated monthly δs (the mixture of δ13 C-CO 2 from all regional end-members) variations. These findings show that the combination of long-term atmospheric carbon isotope observations and inverse modeling can provide a powerful constraint on the carbon cycle of these complex megacities. [ABSTRACT FROM AUTHOR]

Urban areas are global methane (CH4) hotspots. Yet large uncertainties still remain for the CH4 budget of these domains. The Yangtze River Delta (YRD), China, is one of the world's most densely populated regions where a large number of cities are located. To estimate anthropogenic CH4 emissions in YRD, we conducted simultaneous atmospheric CH4 and CO2 mixing ratio measurements from June 2010 to April 2011. By combining these measurements with the Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport models and a priori Emission Database for Global Atmospheric Research emission inventories, we applied three "top-down" approaches to constrain anthropogenic CH4 emissions. These three approaches included multiplicative scaling factors, flux ratio, and scale factor Bayesian inversion. The posteriori CH4 flux density estimated from the three approaches showed high consistency and were 36.32 (±9.17), 35.66 (±2.92), and 36.03(±14.25) nmol·m-2·s-1, respectively, for the duration of the study period (November 2010 to April 2011). The total annual anthropogenic CH4 emission was 6.52(±1.59) Tg for the YRD region based on the average of these three approaches. Our emission estimates were 30.2(±17.6)%, 31.5 (±5.6)%, and 30.8 (±27.4)% lower than the a priori Emission Database for Global Atmospheric Research v432 emission inventory estimate. The scale factor Bayesian inversion results indicate that the overestimate was mainly caused by two source categories including fuel exploitation and agricultural soil emissions (rice cultivation). The posteriori flux densities for agricultural soil and fuel exploitation were 10.68 and 6.34 nmol·m-2·s-1, respectively, and were 47.8% and 29.2% lower than the a priori inventory. Agricultural soil was the largest source contribution and accounted for 29.6% of the YRD CH4 budget during the study period. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) has a global warming potential that is 300 times that of carbon dioxide on a 100-y timescale, and is of major importance for stratospheric ozone depletion. The climate sensitivity of N2O emissions is poorly known, which makes it difficult to project how changing fertilizer use and climate will impact radiative forcing and the ozone layer. Analysis of 6 y of hourly N2O mixing ratios from a very tall tower within the US Corn Belt--one of the most intensive agricultural regions of the world--combined with inverse modeling, shows large interannual variability in N2O emissions (316 Gg N2O-N⋅y-1 to 585 Gg N2O-N⋅y-1). This implies that the regional emission factor is highly sensitive to climate. In the warmest year and spring (2012) of the observational period, the emission factor was 7.5%, nearly double that of previous reports. Indirect emissions associated with runoff and leaching dominated the interannual variability of total emissions. Under current trends in climate and anthropogenic N use, we project a strong positive feedback to warmer and wetter conditions and unabated growth of regional N2O emissions that will exceed 600 Gg N2O-N⋅y-1, on average, by 2050. This increasing emission trend in the US Corn Belt may represent a harbinger of intensifying N2O emissions from other agricultural regions. Such feedbacks will pose a major challenge to the Paris Agreement, which requires large N2O emission mitigation efforts to achieve its goals. [ABSTRACT FROM AUTHOR]

Abstract: Development of optical isotope techniques over the last several years has provided scientists a set of tools for tracing the transport and cycling of CO2 and water vapor between the biosphere and atmosphere. Here, I take a micrometeorological perspective and review these technological advances, assess key instrument performance characteristics, examine how these techniques have been used in the field to improve our understanding of the processes governing the exchange of CO2 and water vapor, and discuss future research directions. Review of the recent literature indicates that: (1) optical techniques have been used to quantify the isotope composition of biosphere–atmosphere exchange using the traditional Keeling mixing line, flux–gradient, eddy covariance, and chamber approaches under a variety of field conditions with near-continuous data records now extending to more than 5-years; (2) high frequency and near continuous isotope measurements at the canopy scale have demonstrated important new insights regarding the behaviour of kinetic fractionation at the leaf versus canopy scales and the controls on ecosystem respiration that could not have been observed previously using traditional methods; (3) based on the assessment of instrument performance, carbon isotope disequilibrium (the difference between the isotope composition of photosynthesis and respiration), carbon turnover rates, and measurement uncertainties, 13C-CO2 investigations are best suited for examining the contributions and changes to ecosystem respiration with a need for more innovative 13C-isotope labeling experiments and compound specific isotope analyses under field conditions; (4) significant progress has been made in measuring the oxygen isotope composition of water vapor fluxes and canopy leaf water enrichment. These new data have provided an opportunity to evaluate models of leaf water enrichment and their application to the canopy scale; and (5) the use of 18O-H2O and 18O-CO2 as tracers of the coupled carbon–water cycle has matured significantly in recent years. Evidence from a range of ecosystems indicates that 18O-CO2 disequilibrium (ranging from 0 to 17‰) is much larger than for 13C-CO2 (typical less than 3‰ in natural C3 ecosystems) making it a useful tracer of coupled carbon and water cycle processes. However, a better understanding of the role of carbonic anhydrase in photosynthetic and respiratory processes under field conditions is now needed in order to make further progress. Finally, the increasing use and development of isotope-enabled land surface schemes along with the acquisition of high temporal resolution isotope data is providing a new opportunity to constrain the carbon and water cycle processes represented in these models. [Copyright &y& Elsevier]

Abstract This paper presents an empirical model of net ecosystem CO2 exchange (NEE) developed for a subarctic fen near Churchill, Manitoba. The model with observed data helps explain the interannual variability in growing season NEE. Five years of tower-flux data are used to test and examine the seasonal behaviour of the model simulations. Processes controlling the observed interannual variability of CO2 exchange at the fen are examined by exploring the sensitivity of the model to changes in air temperature, precipitation and leaf area index. Results indicate that the sensitivity of NEE to changing environmental controls is complex and varies interannually depending on the initial conditions of the wetland. Changes in air temperature and the timing of precipitation events have a strong influence on NEE, which is largely manifest in gross ecosystem photosynthesis (GEP). Climate change scenarios indicate that warmer air temperatures will increase carbon acquisition during wet years but may act to reduce wetland carbon storage in years that experience a large water deficit early in the growing season. Model simulations for this subarctic sedge fen indicate that carbon acquisition is greatest during wet and warm conditions. This suggests therefore that carbon accumulation was greatest at this subarctic fen during its early developmental stages when hydroclimatic conditions were relatively wet and warm at approximately 2500 years before present. [ABSTRACT FROM AUTHOR]

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO 2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO 2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54 μ mol m − 2 s − 1 ) persists for all seasons leading to a 110% overestimate of the ecosystem CO 2 sink (cumulative error of 78 gC m−2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m−2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO 2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m−2) or to systematic over-correction (by 17-37 gC m−2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5 μ mol m − 3 K − 1 . This temperature sensitivity causes CO 2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO 2 measurement errors. [ABSTRACT FROM AUTHOR]