• Energy Research

Abstract. Chemistry in the atmospheric boundary layer (ABL) is controlled by complex processes of surface fluxes, flow, turbulent transport, and chemical reactions. We present a new model SOSA (model to simulate the concentration of organic vapours and sulphuric acid) and attempt to reconstruct the emissions, transport and chemistry in the ABL in and above a vegetation canopy using tower measurements from the SMEAR II at Hyytiälä, Finland and available soundings data from neighbouring meteorological stations. Using the sounding data for upper boundary condition and nudging the model to tower measurements in the surface layer we were able to get a reasonable description of turbulence and other quantities through the ABL. As a first application of the model, we present vertical profiles of organic compounds and discuss their relation to newly formed particles.

SummaryThe alteration of climate is driven not only by anthropogenic activities, but also by biosphere processes that change in conjunction with climate. Emission of volatile organic compounds (VOCs) from vegetation may be particularly sensitive to changes in climate and may play an important role in climate forcing through their influence on the atmospheric oxidative balance, greenhouse gas concentration, and the formation of aerosols. Using the VEMAP vegetation database and associated vegetation responses to climate change, this study examined the independent and combined effects of simulated changes in temperature, CO2 concentration, and vegetation distribution on annual emissions of isoprene, monoterpenes, and other reactive VOCs (ORVOCs) from potential vegetation of the continental United States. Temperature effects were modelled according to the direct influence of temperature on enzymatic isoprene production and the vapour pressure of monoterpenes and ORVOCs. The effect of elevated CO2 concentration was modelled according to increases in foliar biomass per unit of emitting surface area. The effects of vegetation distribution reflects simulated changes in species spatial distribution and areal coverage by 21 different vegetation classes. Simulated climate warming associated with a doubled atmospheric CO2 concentration enhanced total modelled VOC emission by 81.8% (isoprene + 82.1%, monoterpenes + 81.6%, ORVOC + 81.1%), whereas a simulated doubled CO2 alone enhanced total modelled VOC emission by only + 11.8% (isoprene + 13.7%, monoterpenes + 4.1%, ORVOC + 11.7%). A simulated redistribution of vegetation in response to altered temperatures and precipitation patterns caused total modelled VOC emission to decline by 10.4% (isoprene – 11.7%, monoterpenes – 18.6%, ORVOC 0.0%) driven by a decline in area covered by vegetation classes emitting VOCs at high rates. Thus, the positive effect of leaf‐level adjustments to elevated CO2 (i.e. increases in foliar biomass) is balanced by the negative effect of ecosystem‐level adjustments to climate (i.e. decreases in areal coverage of species emitting VOC at high rates).

We are witnessing a crucial change in how we quantify and understand emissions of greenhouse gases and air pollutants, with an increasing demand for science-based transparent emissions information produced by robust community efforts. Today’s scientific capabilities, with near-real-time in-situ and remote sensing observations combined with forward and inverse models and a better understanding of the controlling processes, are contributing to this transformation and providing newapproaches to derive, verify, and forecast emissions (Tong et al., 2011; Frost et al., 2012) and to quantify their impacts on the environment (e.g., Bond et al., 2013). At the same time, the needs for emissions information and the demands for their accuracy and consistency have grown. Changing economies, demographics, agricultural practices, and energy sources, along with mandates to evaluate emissions mitigation efforts, demonstrate compliance with legislation, and verify treaties, are leading to new challenges in emissions understanding. To quote NOAA Senior Technical Scientist David Fahey, “We are in the Century of Accountability. Emissions information is critical not only for environmental science and decision-making, but also as an instrument of foreign policy and international diplomacy.” Emissions quantification represents a key step in explaining observed variability and trends in atmospheric composition and in attributing these observed changes to their causes. Accurate emissions data are necessary to identify feasible controls that reduce adverse impacts associated with air quality and climate and to track the success of implemented policies. To progress further, the international community must improve the understanding of drivers and contributing factors to emissions, and it must strengthen connections among and within different scientific disciplines that characterize our environment and entities that protect the environment and influence further emissions. The Global Emissions InitiAtive, GEIA (http://www.geiacenter. org/), is a center for emissions information exchange and competence building created in 1990 in response to the need for high quality global emissions data (Graedel et al., 1993). While the past two decades have seen considerable progress in developing, improving and assessing emission estimates, emissions continue to be a major contributor to overall uncertainty in atmospheric model simulations. Moving forward, GEIA aims to help build emissions knowledge in a rapidly evolving society by: 1) enhancing understanding, quantification, and analysis of emissions processes; 2) improving access to emissions information; and 3) strengthening the community of emissions groups involved in research, assessment, operations, regulation and policy.

The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB).We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

AbstractWe explore the potential role of atmospheric carbon dioxide (CO2) on isoprene emissions using a global coupled land–atmosphere model [Community Atmospheric Model–Community Land Model (CAM–CLM)] for recent (year 2000, 365 ppm CO2) and future (year 2100, 717 ppm CO2) conditions. We incorporate an empirical model of observed isoprene emissions response to both ambient CO2 concentrations in the long‐term growth environment and short‐term changes in intercellular CO2 concentrations into the MEGAN biogenic emission model embedded within the CLM. Accounting for CO2 inhibition has little impact on predictions of present‐day global isoprene emission (increase from 508 to 523 Tg C yr−1). However, the large increases in future isoprene emissions typically predicted in models, which are due to a projected warmer climate, are entirely offset by including the CO2 effects. Projected global isoprene emissions in 2100 drop from 696 to 479 Tg C yr−1 when this effect is included, maintaining future isoprene sources at levels similar to present day. The isoprene emission response to CO2 is dominated by the long‐term growth environment effect, with modulations of 10% or less due to the variability in intercellular CO2 concentration. As a result, perturbations to isoprene emissions associated with changes in ambient CO2 are largely aseasonal, with little diurnal variability. Future isoprene emissions increase by more than a factor of two in 2100 (to 1242 Tg C yr−1) when projected changes in vegetation distribution and leaf area density are included. Changing land cover and the role of nutrient limitation on CO2 fertilization therefore remain the largest source of uncertainty in isoprene emission prediction. Although future projections suggest a compensatory balance between the effects of temperature and CO2 on isoprene emission, the enhancement of isoprene emission due to lower ambient CO2 concentrations did not compensate for the effect of cooler temperatures over the last 400 thousand years of the geologic record (including the Last Glacial Maximum).

AbstractIsoprene dominates global non-methane volatile organic compound emissions, and impacts tropospheric chemistry by influencing oxidants and aerosols. Isoprene emission rates vary over several orders of magnitude for different plants, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft eddy covariance measurements over the Amazonian forest. We report isoprene emission rates that are three times higher than satellite top-down estimates and 35% higher than model predictions. The results reveal strong correlations between observed isoprene emission rates and terrain elevations, which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can substantially explain isoprene emission variability in tropical forests, and use a model to demonstrate the resulting impacts on regional air quality.

AbstractOne of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth’s energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60–200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon.