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

Abstract

Abstract. 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 19 g kg−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 13 g kg−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 ± 1.2 g kg−1, whereas damp conditions generated the highest EFPM2.5 of all combustion sources in this study, reaching up to 125 ± 23 g kg−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 (7.6–73 g kg−1), followed by traditional mud stoves (5.3–19.7 g kg−1), mud stoves with a chimney for exhaust (3.0–6.8 g kg−1), rocket stoves (1.5–7.2 g kg−1), induced-draft stoves (1.2–5.7 g kg−1), and the bhuse chulo stove (3.2 g kg−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 ± 0.45 g kg−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.

Impact of Changes to the Atmospheric Soluble Iron Deposition Flux on Ocean Biogeochemical Cycles in the Anthropocene

“…The dominant domestic fuel consumed in the PI was wood (Bond et al, ; Fernandes et al, ) and assumed here to be only emitting PM1 (>90% by mass; Kleeman et al, ; Zhang et al, ). An emission factor of 3.5 g[PM1]/kg[wood] consumed (Jayarathne et al, ; Li et al, ) was used to estimate 1850 country‐wise biofuel emissions (Bond et al, ) and subsequently scaled back to 1750 based on human population change estimates (Klein Goldewijk et al, ). Total iron emissions are then based on an assumed iron mass fraction (0.04) in combustion PM1 (Alves et al, ; Schmidl et al, ; Watson & Chow, ; Zhang et al, ).…”

Rooney et al 2019, author responses to reviewer comments

“…The domain is centered over the Palwal District and the SOMAARTH DDESS and includes New Delhi and portions of surrounding states. (Jayarathne et al, 2018) Wood, wooddung mix Average profile of wood and wooddung mix applied to all fuel type emissions.…”

“…The southwest monsoon in summer months in India leads to lower pollution levels than in winter months, which are characterized by low wind speeds, shallow boundary layer depths, and high relative humidity (Sen et al, 2017). With the difficulty in determining representative emissions estimates (Jena et al, 2015;Zhong et al, 2016), simulating the extremely high PM 2.5 observations in the Indo-Gangetic Plain has remained a challenge (Schnell et al, 2018).…”

“…The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al, 2015(Sharma et al, , 2016, an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al (2018b), and PM 2.5 speciation from cooking fires from Jayarathne et al (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain.…”

“…Total PM 2.5 mass emission rates from residential combustion were estimated and distributed by fuel type (wood, dung, or agricultural residue) by University of Illinois. 2 Emitted PM 2.5 weight percent reported byJayarathne et al (2018).3 An average profile applied to all cells, indiscriminate of fuel type.…”