Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data.

Light use efficiency (LUE) is used widely in scaling and modeling contexts. However, the variation and biophysical controls on LUE remain poorly documented. Networks of eddy covariance (EC) towers offer an opportunity to quantify ɛg, the ratio of P, gross primary productivity, to Qa, absorbed photosynthetically active radiation (PAR), across climate zones and vegetation types. Using data from the Fluxnet Canada Research Network (n = 24 sites) in 2004, we examined the relationship between daily and yearly ɛg, driving variables, and site characteristics on a site-specific and plant functional type (PFT) basis using tree regression and linear regression. Data were available for three biomes: grassland, forest, and wetland. Yearly ɛg values ranged from 0.1 to 3.6 g C MJ−1 Qa overall. Daily ɛg was highest in the grassland (daily median ± interquartile range: 3.68 ± 1.98 g C MJ−1 Qa), intermediate in the forested biome (0.84 ± 0.82 g C MJ−1 Qa), and lowest for the wetlands (0.65 ± 0.54 g C MJ−1 Qa). The most important biophysical controls were light and temperature, to the exclusion of water-related variables: a homogeneity of slopes model explained c. 75% of the variation in daily ɛg. For a subset of sites with diffuse PAR data, the ratio of diffuse to total PAR, a proxy for cloudiness, was a key predictor. On the yearly time scale, ɛg was related to leaf area index and mean annual temperature. Aggregating to PFTs did not show functional convergence within any PFT except for the three wetland sites and the Picea mariana toposequence at the daily time step, and when using the Köppen climate classification on a yearly time step. The general lack of conservative daily ɛg behavior within PFTs suggests that PFT-based parameterizations are inappropriate, especially when applied on shorter temporal scales.

Whole ecosystem carbon dioxide (CO2) exchange estimated with the eddy covariance (EC) technique has been central to studies on the responses of terrestrial ecosystems to disturbance and intra-annual and interannual variations in climate, but challenges exist in understanding and reducing the uncertainty in estimates of net ecosystem exchange (NEE) of CO2. We review the potential uncertainties associated with the eddy covariance technique, including systematic errors from insensitivity to high-frequency turbulence, random errors from inadequate sample size associated with averaging period, vertical and horizontal advection issues, and selection criteria for removing periods of inadequate mixing from further analyses. We also discuss benefits and caveats of using independent measurements to evaluate EC-derived NEE, such as comparisons of EC-derived annual NEE and allometric net ecosystem production estimates (NEP) and interpretation of nighttime NEE with scaled chamber-based estimates of ecosystem respiration.

Accurate parameterization of rooting depth is difficult but important for capturing the spatio-temporal dynamics of carbon, water and energy cycles in tropical forests. In this study, we adopted a new approach to constrain rooting depth in terrestrial ecosystem models over the Amazon using satellite data [moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI)] and Biome-BGC terrestrial ecosystem model. We simulated seasonal variations in gross primary production (GPP) using different rooting depths (1, 3, 5, and 10 m) at point and spatial scales to investigate how rooting depth affects modeled seasonal GPP variations and to determine which rooting depth simulates GPP consistent with satellite-based observations. First, we confirmed that rooting depth strongly controls modeled GPP seasonal variations and that only deep rooting systems can successfully track flux-based GPP seasonality at the Tapajos km67 flux site. Second, spatial analysis showed that the model can reproduce the seasonal variations in satellite-based EVI seasonality, however, with required rooting depths strongly dependent on precipitation and the dry season length. For example, a shallow rooting depth (1–3 m) is sufficient in regions with a short dry season (e.g. 0–2 months), and deeper roots are required in regions with a longer dry season (e.g. 3–5 and 5–10 m for the regions with 3–4 and 5–6 months dry season, respectively). Our analysis suggests that setting of proper rooting depths is important to simulating GPP seasonality in tropical forests, and the use of satellite data can help to constrain the spatial variability of rooting depth.

Although mature black spruce forests are a dominant cover type in the boreal forest of North America, it is not clear how their carbon (C) budgets vary across the continent. The installation of an eddy covariance flux tower on an Old Black Spruce (OBS) site in eastern Canada (EOBS, Québec) provided a first opportunity to compare and contrast its annual (2004) and seasonal C exchange with two other pre-existing OBS flux sites from different climatic regions located in Saskatchewan [Southern OBS (SOBS)] and Manitoba [Northern OBS (NOBS)]. Although there was a relatively uniform seasonal pattern of net ecosystem productivity (NEP) among sites, EOBS had a lower total annual NEP than the other two sites. This was primarily because warmer soil under a thicker snowpack at EOBS appeared to increase winter C losses and low light suppressed both NEP and gross ecosystem productivity (GEP) in June. Across sites, greater total annual GEP and ecosystem respiration (R) were associated with greater mean annual air temperatures and an earlier beginning of the growing season. Also, GEP at all three sites showed a stronger relationship with air temperature in spring and early summer compared with later in the growing season, highlighting the importance of springtime conditions to the C budget of these boreal ecosystems. The three sites had different parameter estimates describing the responses of R and GEP at the half hour time scale to near surface temperature and light, respectively. On the other hand, the responses of both R and GEP to temperature at the monthly scale did not differ among sites. These results suggest that a general parameterization could be sufficient at coarse time resolutions to model the response of C exchange to environmental factors of mature black spruce forests from different climatic regions.

Harvard Forest, a rural site located in central Massachusetts downwind of major urban-industrial centers, provides an excellent location to observe a typical regional mixture of anthropogenic trace gases. Air that arrives at Harvard Forest from the southwest is affected by emissions from the U.S. east coast urban corridor and may have residual influence from emissions in the upper Ohio Valley and Great Lakes region farther to the west. Because of its relatively long distance from large individual emission sources, pollution plumes reaching the site are a homogenized mixture of regional anthropogenic emissions. Concentrations of C2-C6 hydrocarbons along with CO and NOy were measured nearly continuously from August 1992 through July 1996 and from June 1999 through November 2001. By correlating observed concentrations to acetylene, which is almost solely produced during combustion, we are able to detect seasonal trends in relative emissions for this series of trace gases. Seasonal changes in n-butane and i-butane emissions may largely be influenced by different gasoline formulations in late spring and summer. Shifts in evaporation rates due to the annual temperature cycle could induce a seasonal pattern for n-pentane, i-pentane and n-hexane emissions. Emissions of ethane and propane lack clear seasonality relative to acetylene emissions and also correlate less with acetylene than other gases, indicating that emissions of these two gases are strongly influenced by sources not associated with fuel combustion. Changes in the observed correlations of CO2 and CO relative to acetylene are consistent with published changes in the estimated emissions of CO2 and CO over the past decade, though variability in the observations makes it difficult to precisely quantify these changes.

We present a decadal (1994–2004) record of carbon dioxide flux in a 160-year-old black spruce forest/veneer bog complex in central Manitoba, Canada. The ecosystem shifted from a source (+41 g C m⁻², 1995) to a sink (−21 g C m⁻², 2004) of CO₂ over the decade, with an average net carbon balance near zero. Annual mean temperatures increased 1–2° during the period, consistent with the decadal trend across the North American boreal biome. We found that ecosystem carbon exchange responded strongly to air temperature, moisture status, potential evapotranspiration, and summertime solar radiation. The seasonal cycle of ecosystem respiration significantly lagged that of photosynthesis, limited by the rate of soil thaw and the slow drainage of the soil column. Factors acting over long time scales, especially water table depth, strongly influenced the carbon budget on annual time scales. Net uptake was enhanced and respiration inhibited by multiple years of rainfall in excess of evaporative demand. Contrary to expectations, we observed no correlation between longer growing seasons and net uptake, possibly because of offsetting increases in ecosystem respiration. The results indicate that the interactions between soil thaw and water table depth provide critical controls on carbon exchange in boreal forests underlain by peat, on seasonal to decadal time scales, and these factors must be simulated in terrestrial biosphere models to predict response of these regions to future climate.

Contemporary emissions of six restricted, ozone-depleting halocarbons, chlorofluorocarbon-11 (CFC-11, CCl3F), CFC-12 (CCl2F2), CFC-113 (CCl2FCClF2), methyl chloroform (CH3CCl3), carbon tetrachloride (CCl4), and Halon-1211 (CBrClF2), and two nonregulated trace gases, chloroform (CHCl3) and sulfur hexafluoride (SF6), are estimated for the United States and Canada. The estimates derive from 900 to 2900 in situ measurements of each of these gases within and above the planetary boundary layer over the United States and Canada as part of the 2003 CO2 Budget and Regional Airborne–North America (COBRA-NA) study. Air masses polluted by anthropogenic sources, identified by concurrently elevated levels of carbon monoxide (CO), SF6, and CHCl3, were sampled over a wide geographical range of these two countries. For each polluted air mass, we calculated emission ratios of halocarbons to CO and employed the Stochastic Time-Inverted Lagrangian Transport (STILT) model to determine the footprint associated with the air mass. Gridded CO emission estimates were then mapped onto the footprints and combined with measured emission ratios to generate footprint-weighted halocarbon flux estimates. We present statistically significant linear relationships between halocarbon fluxes (excluding CCl4) and footprint-weighted population densities, with slopes representative of per capita emission rates. These rates indicate that contemporary emissions of five restricted halocarbons (excluding CCl4) in the United States and Canada continue to account for significant fractions (7–40%) of global emissions.

The long-term resilience of Amazonian forests to climate changes and the fate of their large stores of organic carbon depend on the ecosystem response to climate and weather. This study presents 4 years of eddy covariance data for CO2 and water fluxes in an evergreen, old-growth tropical rain forest examining the forest's response to seasonal variations and to short-term weather anomalies. Photosynthetic efficiency declined late in the wet season, before appreciable leaf litter fall, and increased after new leaf production midway through the dry season. Rates of evapotranspiration were inelastic and did not depend on dry season precipitation. However, ecosystem respiration was inhibited by moisture limitations on heterotrophic respiration during the dry season. The annual carbon balance for this ecosystem was very close to neutral, with mean net loss of 890 ± 220 kg C ha−1 yr−1, and a range of −221 ± 453 (C uptake) to +2677 ± 488 (C loss) kg C ha−1 yr−1 over 4 years. The trend from large net carbon release in 2002 towards net carbon uptake in 2005 implies recovery from prior disturbance. The annual carbon balance was sensitive to weather anomalies, particularly the timing of the dry-to-wet season transition, reflecting modulation of light inputs and respiration processes. Canopy carbon uptake rates were largely controlled by phenology and light with virtually no indication of seasonal water limitation during the 5-month dry season, indicating ample supplies of plant-available-water and ecosystem adaptation for maximum light utilization.

Measurements of carbon monoxide (CO) made as part of three aircraft experiments during the summer of 2004 over North America have been used for the continued validation of the CO retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument on board the Terra satellite. Vertical profiles measured during the NASA INTEX-A campaign, designed to be coincident with MOPITT overpasses, as well as measurements made during the COBRA-2004 and MOZAIC experiments, provided valuable validation comparisons. On average, the MOPITT CO retrievals are biased slightly high for these North America locations. While the mean bias differs between the different aircraft experiments (e.g., 7.0 ppbv for MOZAIC to 18.4 ppbv for COBRA at 700 hPa), the standard deviations are quite large, so the results for the three data sets can be considered consistent. On average, it is estimated that MOPITT is 7–14% high at 700 hPa and ~3% high at 350 hPa. These results are consistent with the validation results for the Carr, Colorado, Harvard Forest, Massachusetts, and Poker Flats, Alaska, aircraft profiles for “phase 2” presented by Emmons et al. (2004) and are generally within the design criteria of 10% accuracy.

The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO ₂ flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production

We used a 10-year record of the CO2 flux by an old growth boreal forest in central Manitoba (the Northern Old Black Spruce Site (NOBS)), a ∼150-year-old Picea mariana [Mill.] stand) to determine whether and how whole-forest CO2 flux is related to tree ring width. We compared a 37-year ring width chronology collected at NOBS to a second chronology that was collected at a nearby Black Spruce stand with a different disturbance history, and also to three measures of annual whole-forest photosynthesis [gross ecosystem production (GEP)], two measures of annual respiration (R), and one measure of annual carbon balance [net ecosystem production (NEP)]. The year-to-year ring width fluctuations were well correlated between the two sites; increasing our confidence in the NOBS chronology and implying that ring width variation is driven and synchronized by the physical environment. Both chronologies exhibited serial correlation, with a fluctuation in ring width that had an apparent periodicity of ∼7 years. Neither chronology was correlated with variation in annual precipitation or temperature. Ring width and NEP increased, while R decreased from 1995 to 2004. GEP either remained constant or decreased from 1995 to 2004, depending on which measure was considered. The lack of relationship between ring width and GEP may indicate that ring growth is controlled almost entirely by something other than carbon uptake. Alternative explanations for the ring width chronologies include the possibility that wood production varies as a result of shifts in respiration, or that an unidentified aspect of the environment, rather than the balance between GEP and respiration, controls wood production. The serial correlation in ring width may be related to increases and decreases in carbohydrate pools, or to gradual changes in nutrient availability, pathogens, herbivores, soil frost or soil water table. The cause or causes of serial correlation, and the controls on the allocation of photosynthate to wood production, emerge as critical uncertainties for efforts in predicting the carbon balance of boreal ecosystems and inferring past climate from tree rings.

We utilized eddy-covariance observations of carbon dioxide (CO2) and water vapor exchange at three AmeriFlux mid-latitude forest stands to evaluate IBIS, a Dynamic Global Vegetation Model (DGVM). Measurements of leaf area index (LAI), soil moisture and temperature, runoff, soil carbon (C), and soil respiration (R) were also compared with model output. An experimental approach was designed to help attribute model errors to the vegetation dynamics and phenology formulations versus simulated biological processes. Continental scale phenology sub-models poorly represented the timing of budburst and evolution of canopy LAI in deciduous forests. Biases of vegetation green-up of 6 weeks and delayed senescence were noted. Simulated soil temperatures were overestimated (underestimated) during the summer (winter) on average by 2–5 °C. Ecosystem R was overestimated during the growing season, on average, by 20–60 g C m−2 month−1, and underestimated during the winter by 10–20 g C m−2 month−1 at all sites. Simulated soil R failed to capture observed mid-summer peak rates and was generally lower than observed in winter. The overall comparison of simulated net ecosystem production (NEP) to observations showed a significant underestimate of growing season NEP of 25–100 g C m−2 month−1, and an overall positive bias of 10–40 g C m−2 month−1 during the winter. Excellent agreement between annual average NEP observations and IBIS simulations in “fixed vegetation” mode resulted from offsetting seasonal model biases. The magnitude of simulated variation in seasonal and inter-annual C exchange was generally dampened with respect to observations. The parameterization, and in some cases the formulations (e.g., ecosystem R and phenology) limited model capacity to capture the seasonal fluctuations of C and water exchange. Model parameterizations and formulations were originally constrained and generalized for application to a wide range of global climate and soil conditions and plant functional types (PFTs), likely contributing to model biases. This problem potentially applies to other DGVMs and biosphere models, and will likely become increasingly relevant if investigators apply their models at higher spatial resolution. We suggest that revisions to DGVMs should focus on advancing the capabilities of current phenology formulations to account for photoperiod, soil moisture and frost in addition to temperature. Model representations of PFTs and formulations of ecosystem R need to be rethought, particularly with respect to use of Q10 temperature functions as modifiers. Surface energy balance, C allocation, soil R, and plant response to nutrient stress deserve attention as well.

Global estimates of terrestrial gross primary production (GPP) are now operationally produced from Moderate Resolution Imaging Spectrometer (MODIS) imagery at the 1-km spatial resolution and eight-day temporal resolution. In this study, MODIS GPP products were compared with ground-based GPP estimates over multiple years at three sites-a boreal conifer forest, a temperate deciduous forest, and a desert grassland. The ground-based estimates relied on measurements at eddy covariance flux towers, fine resolution remote sensing, and modeling. The MODIS GPP showed seasonal variation that was generally consistent with the in situ observations. The sign and magnitude of year-to-year variation in the MODIS products agreed with that of the ground observations at two of the three sites. Examination of the inputs to the MODIS GPP algorithm-notably the fraction of photosynthetically active radiation (FPAR) that is absorbed by the canopy), minimum temperature scalar, and vapor pressure deficit scalar-provided explanations for cases of disagreement between the MODIS and ground-based GPP estimates. Continued evaluation of interannual variation in MODIS products and related climate variables will aid in assessing potential biospheric feedbacks to climate change

The spatial and temporal gradients in atmospheric CO₂ contain signatures of carbon fluxes, and as part of inverse studies, these signatures have been combined with atmospheric models to infer carbon sources and sinks. However, such studies have yet to yield finer-scale, regional fluxes over the continent that can be linked to ecosystem processes and ground-based observations. The reasons for this gap are twofold: lack of atmospheric observations over the continent and model deficiencies in interpreting such observations.

We present the Vegetation Photosynthesis and Respiration Model (VPRM), a satellite-based assimilation scheme that estimates hourly values of Net Ecosystem Exchange (NEE) of CO2 for 12 North American biomes using the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), derived from reflectance data of the Moderate Resolution Imaging Spectroradiometer (MODIS), plus high-resolution data for sunlight and air temperature. The motivation is to provide reliable, fine-grained first-guess fields of surface CO2 fluxes for application in inverse models at continental and smaller scales. An extremely simple mathematical structure, with minimal numbers of parameters, facilitates optimization using in situ data, with finesse provided by maximal infusion of observed NEE and environmental data from networks of eddy covariance towers across North America (AmeriFlux and Fluxnet Canada). Cross validation showed that the VPRM has strong prediction ability for hourly to monthly timescales for sites with similar vegetation. The VPRM also provides consistent partitioning of NEE into Gross Ecosystem Exchange (GEE, the light-dependent part of NEE) and ecosystem respiration (R, the light-independent part), half-saturation irradiance of ecosystem photosynthesis, and annual sum of NEE at all eddy flux sites for which it is optimized. The capability to provide reliable patterns of surface flux for fine-scale inversions is presently limited by the number of vegetation classes for which NEE can be constrained by the current network of eddy flux sites and by the accuracy of MODIS data and data for sunlight.

Net ecosystem productivity (NEP) during August 2003 was measured by using eddy covariance above 17 forest and 3 peatland sites along an east–west continental-scale transect in Canada. Measured sites included recently disturbed stands, young forest stands, intermediate-aged conifer stands, mature deciduous stands, mature conifer stands, fens, and an open shrub bog. Diurnal courses of NEP showed strong coherence within the different ecosystem categories. Recently disturbed sites showed the weakest diurnal cycle; and intermediate-aged conifers, the strongest. The western treed fen had a more pronounced diurnal pattern than the eastern shrub bog or the Saskatchewan patterned fen. All but three sites were clearly afternoon C sinks. Ecosystem respiration was highest for the young fire sites. The intermediate-aged conifer sites had the highest maximum NEP (NEPmax) and gross ecosystem productivity (GEPmax), attaining rates that would be consistent with the presence of a strong terrestrial C sink in regions where these types of forest are common. These results support the idea that large-scale C cycle modeling activities would benefit from information on the age-class distribution and disturbance types within larger grid cells. Light use efficiency followed a pattern similar to that of NEPmax and GEPmax. Four of the five recently disturbed sites and all three of the peatland sites had low water use efficiencies.

We analyze the potential for inferring spatially resolved surface fluxes from atmospheric tracer observations within the mixed layer, such as from monitoring towers, using a receptor oriented transport model (Stochastic Time-Inverted Lagrangian Transport model - STILT) coupled to a simple biosphere in which CO₂ fluxes are represented as functional responses to environmental drivers (radiation and temperature). Transport and biospheric fluxes are coupled on a dynamic grid using a polar projection with high horizontal resolution (~20 km) in near field, and low resolution far away (as coarse as 2000 km), reducing the number of surface pixels without significant loss of information. To test the system, and to evaluate the errors associated with the retrieval of fluxes from atmospheric observations, a pseudo data experiment was performed. A large number of realizations of measurements (pseudo data) and a priori fluxes were generated, and for each case spatially resolved fluxes were retrieved. Results indicate strong potential for high resolution retrievals based on a network of tall towers, subject to the requirement of correctly specifying the a priori uncertainty covariance, especially the off diagonal elements that control spatial correlations. False assumptions about the degree to which the uncertainties in the a priori fluxes are spatially correlated may lead to a strong underestimation of uncertainties in the retrieved fluxes, or, equivalently, to biased retrievals. The framework presented here, however, allows a conservative choice of the off diagonal elements that avoids biasing the retrievals.

Woody debris (WD) is an important component of forest C budgets, both as a C reservoir and source of CO2 to the atmosphere. We used an infrared gas analyzer and closed dynamic chamber to measure CO(2) efflux from downed coarse WD (CWD; diameter>or=7.5 cm) and fine WD (FWD; 7.5 cm>diameter>or=2 cm) to assess respiration in a selectively logged forest and a maturing forest (control site) in the northeastern USA. We developed two linear regression models to predict WD respiration: one based on WD temperature, moisture, and size (R2=0.57), and the other on decay class and air temperature (R2=0.32). WD respiration (0.28+/-0.09 Mg C ha-1 year-1) contributed only approximately 2% of total ecosystem respiration (12.3+/-0.7 Mg C ha-1 year-1, 1999-2003), but net C flux from CWD accounted for up to 30% of net ecosystem exchange in the maturing forest. C flux from CWD on the logged site increased modestly, from 0.61+/-0.29 Mg C ha-1 year-1 prior to logging to 0.77+/-0.23 Mg C ha-1 year-1 after logging, reflecting increased CWD stocks. FWD biomass and associated respiration flux were approximately 7 times and approximately 5 times greater, respectively, in the logged site than the control site. The net C flux associated with CWD, including inputs and respiratory outputs, was 0.35+/-0.19 Mg C ha-1 year-1 (net C sink) in the control site and -0.30+/-0.30 Mg C ha-1 year-1 (net C source) in the logged site. We infer that accumulation of WD may represent a small net C sink in maturing northern hardwood forests. Disturbance, such as selective logging, can enlarge the WD pool, increasing the net C flux from the WD pool to the atmosphere and potentially causing it to become a net C source.

We report concentrations of atmospheric NO_x, nitric acid (HNO₃), peroxyacetyl nitrate (PAN), and NO_y; eddy covariance fluxes of NO_x and NO_y; inferred fluxes of HNO₃ at the mixed deciduous Harvard Forest field site, June–November 2000. A novel Tunable Diode Laser Absorption Spectrometer (TDLAS) produced sensitive, hourly HNO₃ concentration data, which were used to evaluate systematic error in the Dry Deposition Inferential Method (DDIM), often employed to estimate weekly HNO₃ flux at deposition monitoring network sites. Due to the weak diurnal variation in HNO₃ concentration at Harvard Forest, no systematic bias was found in the application of this method to compute daily and weekly average fluxes. The sum of individually measured reactive nitrogen species concentrations and fluxes were approximately equal to total NO_y concentrations and fluxes for clean Northwesterly flows, but fell short of the total NO_y values for the more polluted Southwesterly transport regime. The concentration and deposition velocity of the unmeasured reactive nitrogen compounds were consistent with prior estimates and recent measurements of alkyl- and hydroxyalkyl nitrates, suggesting that these compounds play an important role in reactive nitrogen deposition processes where anthropogenic NO_x emissions and natural hydrocarbons are present.