Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal

Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emissions (IVE) model with local emissions factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emissions factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. HTAP_v2.2 does not include the brick sector and we found that our sulfur dioxide (SO2) emissions estimates from brick kilns are comparable to 70 % of the total SO2 emissions considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emissions scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model\u27s boundary layer representation, to capture strong spatial gradients of air pollutant concentrations

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

The Global N20 Model Intercomparison Project

Nitrous oxide (N2O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and spatiotemporal patterns of N2O fluxes and the key drivers of N2O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N2O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N2O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N2O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N2O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N2O dynamics; and 3) provide a benchmarking estimate of N2O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N2O estimation derived from the NMIP is a key component of the global N2O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative

Weakened growth of cropland‐N2O emissions in China associated with nationwide policy interventions

This study was supported by the National Natural Science Foundation of China (41671464; 7181101181), the National Key Research and Development Program of China (2016YFD0800501; 2018YFC0213304), 111 Project (B14001), the GCP-INI Global N2O Budget and the INMS Asia Demo Activities. The input of P.S. contributes to the UK-China Virtual Joint Centre on Nitrogen ìN-Circleî funded by the Newton Fund via UK BBSRC/NERC (BB/N013484/1). We acknowledged Eric Ceschia, Kristiina Regina, Dario Papale, and the NANORP for sharing a part of observation data.Peer reviewedPostprin

Corrigendum to "Global and regional emission estimates for HCFC-22", Atmos. Chem. Phys., 12, 10033–10050, 2012

No abstract available

Effectiveness of state climate and energy policies in reducing power sector CO2 emissions dataset

This provides a dataset of the adoption of 17 different climate and energy policies by each of the 50 states in the U.S. for the period 1990-2014 based on state-specific information from C2ES (2017) and Morey and Kirsch (2016). Each of the policy variables are set to zero before adoption and one after adoption. This new dataset also incorporates a time-series data on electricity price [USD], population, and CO2 emitted in the electricity sector [metric ton, MT] for each state. During data processing, we also created two variables, named export ratio and emissions intensity. Export ratio is the percentage of a state's total electricity production that is exported to other states. It is set to zero if it a state is a net importer of electricity. We derived the state-level emissions intensity from EIA's "Net Generation by State by Type of Producer by Energy Source" (EIA 2016) and EPA's "State CO2 Emissions from Fossil Fuel Combustion, 1990-2014" (EPA 2016) reports. To determine a state's emissions intensity, we divided state-level electric power sector CO2 emissions [in million metric tons, MMT] by state-level electric power industry generation [MWh] for each year from 1990-2014. By 2014, Connecticut, New York, and Oregon have adopted 10 or more policies and some, including climate action plan and binding Renewable Portfolio Standards have been adopted by more than 30 states. This new dataset can be used to assess the effectiveness of different policies on reducing emissions from the electricity sector and bring insights into policy adoption to mitigate climate change within the United States