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 870 nm) 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 <i>B</i>_scat, EF <i>B</i>_abs, in m² kg⁻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 (g kg⁻¹ fuel burned). The trace gas measurements provide EFs (g kg⁻¹) for CO₂, CO, CH₄, selected non-methane hydrocarbons up to C₁₀, a large suite of oxygenated organic compounds, NH₃, HCN, NO_<i>x</i>, SO₂, HCl, HF, etc. (up to ∼ 80 gases in all). <br><br> 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 ± 1.33 g kg⁻¹), organic acids (7.66 ± 6.90 g kg⁻¹), and HCN (2.01 ± 1.25 g kg⁻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- (∼ 4.5 g kg⁻¹) and wood-fuel (∼ 1.5 g kg⁻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 (∼ 12 g kg⁻¹) and SO₂ (2.54 ± 1.09 g kg⁻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 NO_<i>x</i>, 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 ± 0.2 g kg⁻¹. Mixed-garbage burning produced significantly more BC (3.3 ± 3.88 g kg⁻¹) and BTEX (∼ 4.5 g kg⁻¹) emissions than in previous measurements. For all fossil fuel sources, diesel burned more efficiently than gasoline but produced larger NO_<i>x</i> 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 ∼ 700 g kg⁻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