Process Modeling of Global Soil Nitrous Oxide Emissions

http://globalchange.mit.edu/research/publications/2213Nitrous oxide is an important greenhouse gas and is a major ozone-depleting substance. To understand and quantify soil nitrous oxide emissions, we expanded the Community Land Model with prognostic Carbon and Nitrogen (CLM-CN) by inserting a module to estimate annually- and seasonally-varying nitrous oxide emissions between 1978 and 2000. We evaluate our soil N2O emission estimates against existing emissions inventories, other process-based model estimates, and observations from two forest sites in the Amazon and one in the United States. The model reproduces soil temperature and soil moisture relatively well, and it reconfirms the important relationship between N2O emissions and these parameters. The model also reproduces observations of N2O emissions well in the Amazonian forests but not during the winter in the USA. Applying this model to estimate the past 23 years of global soil N2O emissions, we find that there is a significant decrease in soil N2O emissions associated with drought and El Ni˜no years. More study is necessary to quantify the high-latitude winter activity in the model in order to better understand the impact of future climate on N2O emissions and vice versa.NASA Upper Atmosphere Research Program grants NNX11AF17G and NNX07AE89

The Impact of Coordinated Policies on Air Pollution Emissions from Road Transportation in China

Improving air quality across mainland China is an urgent policy challenge. While much of the problem is linked to China’s broader reliance on coal and other fossil fuels across the energy system, road transportation is an important and growing source of air pollution. Here we use an energy-economic model, embedded in the broader Regional Emissions Air Quality Climate and Health (REACH) modeling framework, to analyze the impacts of implementing vehicle emissions together with a broader economy-wide climate policy on total air pollution and its spatial distribution. We find that full and immediate implementation of existing vehicle emissions standards at China 3/III level or tighter will significantly reduce the contribution of transportation to degraded air quality by 2030. We further show that transportation emissions standards function as an important complement to an economy-wide price on CO2, which delivers significant co-benefits for air pollution reduction that are concentrated primarily in non-transportation sectors. Going forward, vehicle emissions standards and an economy-wide carbon price form a highly effective coordinated policy package that supports China’s air quality and climate change mitigation goals.Research Partners: Emory University, Tsinghua University, and Massachusetts Institute of Technology. This research builds on the work of the MIT-Tsinghua China Energy and Climate Project. The China Energy and Climate Project (CECP) involves close collaboration and personnel exchange between the MIT Joint Program on the Science and Policy of Global Change and the Institute for Energy, Environment and Economy at Tsinghua University

The impact of China's vehicle emissions on regional air quality in 2000 and 2020: a scenario analysis

The number of vehicles in China has been increasing rapidly. We evaluate the impact of current and possible future vehicle emissions from China on Asian air quality. We modify the Regional Emission Inventory in Asia (REAS) for China's road transport sector in 2000 using updated Chinese data for the number of vehicles, annual mileage, and emission factors. We develop two scenarios for 2020: a scenario where emission factors remain the same as they were in 2000 (No-Policy, NoPol), and a scenario where Euro 3 vehicle emission standards are applied to all vehicles (except motorcycles and rural vehicles). The Euro 3 scenario is an approximation of what may be the case in 2020 as, starting in 2008, all new vehicles in China (except motorcycles) were required to meet the Euro 3 emission standards. Using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), we examine the regional air quality response to China's vehicle emissions in 2000 and in 2020 for the NoPol and Euro 3 scenarios. We evaluate the 2000 model results with observations in Japan, China, Korea, and Russia. Under NoPol in 2020, emissions of carbon monoxide (CO), nitrogen oxides (NO<sub>x</sub>), non-methane volatile organic compounds (NMVOCs), black carbon (BC), and organic carbon (OC) from China's vehicles more than double compared to the 2000 baseline. If all vehicles meet the Euro 3 regulations in 2020, however, these emissions are reduced by more than 50% relative to NoPol. The implementation of stringent vehicle emission standards leads to a large, simultaneous reduction of the surface ozone (O<sub>3</sub>) mixing ratios and particulate matter (PM<sub>2.5</sub>) concentrations. In the Euro 3 scenario, surface O<sub>3</sub> is reduced by more than 10 ppbv and surface PM<sub>2.5</sub> is reduced by more than 10 μg m<sup>−3</sup> relative to NoPol in Northeast China in all seasons. In spring, surface O<sub>3</sub> mixing ratios and PM<sub>2.5</sub> concentrations in neighboring countries are also reduced by more than 3 ppbv and 1 μg m<sup>−3</sup>, respectively. We find that effective regulation of China's road transport sector will be of significant benefit for air quality both within China and across East Asia as well

TransCom N2O model inter-comparison - Part 2:Atmospheric inversion estimates of N2O emissions

This study examines N2O emission estimates from five different atmospheric inversion frameworks based on chemistry transport models (CTMs). The five frameworks differ in the choice of CTM, meteorological data, prior uncertainties and inversion method but use the same prior emissions and observation data set. The posterior modelled atmospheric N2O mole fractions are compared to observations to assess the performance of the inversions and to help diagnose problems in the modelled transport. Additionally, the mean emissions for 2006 to 2008 are compared in terms of the spatial distribution and seasonality. Overall, there is a good agreement among the inversions for the mean global total emission, which ranges from 16.1 to 18.7 TgN yr(-1) and is consistent with previous estimates. Ocean emissions represent between 31 and 38% of the global total compared to widely varying previous estimates of 24 to 38%. Emissions from the northern mid- to high latitudes are likely to be more important, with a consistent shift in emissions from the tropics and subtropics to the mid- to high latitudes in the Northern Hemisphere; the emission ratio for 0-30A degrees N to 30-90A degrees N ranges from 1.5 to 1.9 compared with 2.9 to 3.0 in previous estimates. The largest discrepancies across inversions are seen for the regions of South and East Asia and for tropical and South America owing to the poor observational constraint for these areas and to considerable differences in the modelled transport, especially inter-hemispheric exchange rates and tropical convective mixing. Estimates of the seasonal cycle in N2O emissions are also sensitive to errors in modelled stratosphere-to-troposphere transport in the tropics and southern extratropics. Overall, the results show a convergence in the global and regional emissions compared to previous independent studies

Uncertainties in emissions estimates of greenhouse gases and air pollutants in India and their impacts on regional air quality

Greenhouse gas and air pollutant precursor emissions have been increasing rapidly in India. Large uncertainties exist in emissions inventories and quantification of their uncertainties is essential for better understanding of the linkages among emissions and air quality, climate, and health. We use Monte Carlo methods to assess the uncertainties of the existing carbon dioxide (CO2), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) emission estimates from four source sectors for India. We also assess differences in the existing emissions estimates within the nine subnational regions. We find large uncertainties, higher than the current estimates for all species other than CO, when all the existing emissions estimates are combined. We further assess the impact of these differences in emissions on air quality using a chemical transport model. More efforts are needed to constrain emissions, especially in the Indo-Gangetic Plain, where not only the emissions differences are high but also the simulated concentrations using different inventories. Our study highlights the importance of constraining SO2, NOx, and NH3 emissions for secondary PM concentrations

Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of particulate matter from wood-and dung-fueled cooking fires, garbage and crop residue burning, brick kilns, and other sources

The Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) characterized widespread and under-sampled combustion sources common to South Asia, including brick kilns, garbage burning, diesel and gasoline generators, diesel groundwater pumps, idling motorcycles, traditional and modern cooking stoves and fires, crop residue burning, and heating fire. Fuel-based emission factors (EFs; with units of pollutant mass emitted per kilogram of fuel combusted) were determined for fine particulate matter (PM2.5), organic carbon (OC), elemental carbon (EC), inorganic ions, trace metals, and organic species. For the forced-draft zigzag brick kiln, EFPM2.5 ranged from 12 to 19gkg-1 with major contributions from OC (7%), sulfate expected to be in the form of sulfuric acid (31.9%), and other chemicals not measured (e.g., particle-bound water). For the clamp kiln, EFPM2.5 ranged from 8 to 13gkg-1, with major contributions from OC (63.2%), sulfate (23.4%), and ammonium (16%). Our brick kiln EFPM2.5 values may exceed those previously reported, partly because we sampled emissions at ambient temperature after emission from the stack or kiln allowing some particle-phase OC and sulfate to form from gaseous precursors. The combustion of mixed household garbage under dry conditions had an EFPM2.5 of 7.4±1.2gkg-1, whereas damp conditions generated the highest EFPM2.5 of all combustion sources in this study, reaching up to 125±23gkg-1. Garbage burning emissions contained triphenylbenzene and relatively high concentrations of heavy metals (Cu, Pb, Sb), making these useful markers of this source. A variety of cooking stoves and fires fueled with dung, hardwood, twigs, and/or other biofuels were studied. The use of dung for cooking and heating produced higher EFPM2.5 than other biofuel sources and consistently emitted more PM2.5 and OC than burning hardwood and/or twigs; this trend was consistent across traditional mud stoves, chimney stoves, and three-stone cooking fires. The comparisons of different cooking stoves and cooking fires revealed the highest PM emissions from three-stone cooking fires (7.6-73gkg-1), followed by traditional mud stoves (5.3-19.7gkg-1), mud stoves with a chimney for exhaust (3.0-6.8gkg-1), rocket stoves (1.5-7.2gkg-1), induced-draft stoves (1.2-5.7gkg-1), and the bhuse chulo stove (3.2gkg-1), while biogas had no detectable PM emissions. Idling motorcycle emissions were evaluated before and after routine servicing at a local shop, which decreased EFPM2.5 from 8.8±1.3 to 0.71±0.45gkg-1 when averaged across five motorcycles. Organic species analysis indicated that this reduction in PM2.5 was largely due to a decrease in emission of motor oil, probably from the crankcase. The EF and chemical emissions profiles developed in this study may be used for source apportionment and to update regional emission inventories

Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of trace gases and light-absorbing carbon from wood and dung cooking fires, garbage and crop residue burning, brick kilns, and other sources

The Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) campaign took place in and around the Kathmandu Valley and in the Indo-Gangetic Plain (IGP) of southern Nepal during April 2015. The source characterization phase targeted numerous important but undersampled (and often inefficient) combustion sources that are widespread in the developing world such as cooking with a variety of stoves and solid fuels, brick kilns, open burning of municipal solid waste (a.k.a. trash or garbage burning), crop residue burning, generators, irrigation pumps, and motorcycles. NAMaSTE produced the first, or rare, measurements of aerosol optical properties, aerosol mass, and detailed trace gas chemistry for the emissions from many of the sources. This paper reports the trace gas and aerosol measurements obtained by Fourier transform infrared (FTIR) spectroscopy, whole-air sampling (WAS), and photoacoustic extinctiometers (PAX; 405 and 870nm) based on field work with a moveable lab sampling authentic sources. The primary aerosol optical properties reported include emission factors (EFs) for scattering and absorption coefficients (EF Bscat, EF Babs, inm2kg-1 fuel burned), single scattering albedos (SSAs), and absorption Ångström exponents (AAEs). From these data we estimate black and brown carbon (BC, BrC) emission factors (gkg-1 fuel burned). The trace gas measurements provide EFs (gkg-1) for CO2, CO, CH4, selected non-methane hydrocarbons up to C10, a large suite of oxygenated organic compounds, NH3, HCN, NOx, SO2, HCl, HF, etc. (up to ∼ 80 gases in all). The emissions varied significantly by source, and light absorption by both BrC and BC was important for many sources. The AAE for dung-fuel cooking fires (4.63±0.68) was significantly higher than for wood-fuel cooking fires (3.01±0.10). Dung-fuel cooking fires also emitted high levels of NH3 (3.00±1.33gkg-1), organic acids (7.66±6.90gkg-1), and HCN (2.01±1.25gkg-1), where the latter could contribute to satellite observations of high levels of HCN in the lower stratosphere above the Asian monsoon. HCN was also emitted in significant quantities by several non-biomass burning sources. BTEX compounds (benzene, toluene, ethylbenzene, xylenes) were major emissions from both dung- (∼4.5gkg-1) and wood-fuel (∼1.5gkg-1) cooking fires, and a simple method to estimate indoor exposure to the many measured important air toxics is described. Biogas emerged as the cleanest cooking technology of approximately a dozen stove-fuel combinations measured. Crop residue burning produced relatively high emissions of oxygenated organic compounds (∼12gkg-1) and SO2 (2.54±1.09gkg-1). Two brick kilns co-firing different amounts of biomass with coal as the primary fuel produced contrasting results. A zigzag kiln burning mostly coal at high efficiency produced larger amounts of BC, HF, HCl, and NOx, with the halogenated emissions likely coming from the clay. The clamp kiln (with relatively more biomass fuel) produced much greater quantities of most individual organic gases, about twice as much BrC, and significantly more known and likely organic aerosol precursors. Both kilns were significant SO2 sources with their emission factors averaging 12.8±0.2gkg-1. Mixed-garbage burning produced significantly more BC (3.3±3.88gkg-1) and BTEX (∼4.5gkg-1) emissions than in previous measurements. For all fossil fuel sources, diesel burned more efficiently than gasoline but produced larger NOx and aerosol emission factors. Among the least efficient sources sampled were gasoline-fueled motorcycles during start-up and idling for which the CO EF was on the order of ∼700gkg-1 - or about 10 times that of a typical biomass fire. Minor motorcycle servicing led to minimal if any reduction in gaseous pollutants but reduced particulate emissions, as detailed in a companion paper (Jayarathne et al., 2016). A small gasoline-powered generator and an insect repellent fire were also among the sources with the highest emission factors for pollutants. These measurements begin to address the critical data gap for these important, undersampled sources, but due to their diversity and abundance, more work is needed

Comparison of Emissions Inventories of Anthropogenic Air Pollutants in China

Anthropogenic air pollutant emissions have been increasing rapidly in China. Modelers use emissions inventories to assess temporal and spatial distribution of these emissions to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates and assessing discrepancies in these inventories is essential for better understanding of the trends in air pollution over China. We compare five different emissions inventories estimating emissions of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter with an aerodynamic diameter of 10 um or less (PM10) from China. The emissions inventories analyzed in this paper include Regional Emissions inventory in ASia v2.1 (REAS); Multi-resolution Emission Inventory for China (MEIC); Emission Database for Global Atmospheric Research v4.2 (EDGAR); the inventory by Yu Zhao (ZHAO); and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008 during which the Chinese economic activities have more than doubled. In addition to the national total, we also analyzed emissions from four source sectors (industry, transportation, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements (~ seven fold) exist among the five inventories at disaggregated levels. These discrepancies lead to differences of 67 ug/m3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modelled regional concentrations in China. We also find that MEIC inventory emissions estimates create a VOC-limited environment that produces much lower O3 mixing ratio in the East and Central China compared to the simulations using REAS and EDGAR estimates. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding an effective mitigation measure for reducing national and regional air pollution in China