Effects of wood moisture on emission factors for PM2.5, particle numbers and particulate-phase PAHs from Eucalyptus globulus combustion using a controlled combustion chamber for emissions

Guerrero, Fabián; Yáñez, Karen; Vidal, Víctor; Cereceda-Balic, Francisco

doi:10.1016/j.scitotenv.2018.08.057

Cited by 29 publications

(17 citation statements)

References 53 publications

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“…Among other factors, the EFs vary according to the efficiency of the technology used (e.g., fireplace, wood stove, simple heater, heater with temper, etc. ), the humidity present in the wood, and the device's operating conditions 1 (Jimenez et al, 2017;Guerrero et al, 2019;Schuefftan et al, 2016). For CO and NMVOC's (Non-Methane VOCs) we use EFs for dry firewood from EMEP/EEA (2019;) while for CH4 the EFs estimated on the tier 1 approach from IPCC ( 2006) are used.…”

Section: Residential Sectormentioning

confidence: 99%

“…Denier van der Gon et al,2015). Moreover, these emission factors do not consider wet firewood and combustion with poor operating conditions which considerably increases these pollutants' emissions (Schueftan et al, 2016;Guerrero et al., 2019). The current inventory (INEMA) however, considers emission factors that take these conditions into account.…”

Section: Comparison Of Total Emissions By Sector and Pollutant With Edgar Inventorymentioning

confidence: 99%

“…The final EF's used in this study results from aggregating several EF each one of which corresponds to specific emission conditions, and/or fuel components that determine the magnitude of the emitted flux, by weighting each EF according to distribution parameters estimated on household surveys. The most relevant parameters considered are, among others, the quality and efficiency of the used technology (appliance type), the tree species, the humidity of firewood fuel, and the operating conditions of devices (Jimenez et al, 2017;Guerrero et al, 2019;Schuefftan et al, 2016). Each of these EFs has its uncertainty, which depends on the quality and the number of laboratory tests carried out to determine its robustness (RTI International, 2007).…”

Section: Uncertainty and Quality Of Estimations On The Residential Sectormentioning

confidence: 99%

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High resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential sectors of Chile

Álamos

Huneeus

Opazo

et al. 2021

Preprint

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Abstract. This study presents the first high-resolution national inventory of anthropogenic emissions for Chile (INEMA). Emissions for vehicular, industrial, energy, mining and residential sectors are estimated for the period 2015–2017 and spatially distributed onto a high-resolution grid (1 × 1 km approximately). The pollutants included are CO2, NOx, SO2, CO, VOCs, NH3, and particulate matter (PM10 and PM2.5) for all sectors. CH4 and Black Carbon are included for transport and residential sources, while Arsenic, Benzene, Mercury, Lead, Toluene, and Polychlorinated dibenzo-p-dioxins and Furan (PCDD / F) are estimated for energy, mining and industrial sources. New activity data and emissions factors are compiled to estimate emissions, which are subsequently spatially distributed using census data and Chile's road network information. The estimated total annual national emissions of PM10 and PM2.5 are 191 and 173 kilotonnes (Kt) , respectively. The residential sector is responsible for over 90 % of these emissions. This sector also emits 81 % and 87 % of total CO and VOC, respectively. Additionally, the energy and industry sectors contribute significantly to NH3, SO2, CO2 emissions while the transport sector dominates NOx and CO2 emissions, and the Mining sector dominates SO2 emissions. In general, emissions of anthropogenic air pollutants and CO2 in northern Chile are dominated by mining activities as well as thermoelectric power plants while in central chile the dominant sources are transport and residential emissions. The latter also mostly dominates emissions in southern Chile which has a much colder climate. Preliminary analysis revealed the dominant role of the emission factors in the final emission uncertainty. Nevertheless, uncertainty in activity also contributes, as suggested by the difference in CO2 emissions between INEMA and EDGAR. A comparison between these two inventories also revealed considerable differences for all pollutants in terms of magnitude and sectoral contribution, especially for the residential sector. EDGAR presents larger emissions for most of the pollutants except for CH4 and PM2.5. The differences between both inventories can partly be explained by the use of different emission factors, in particular for the residential sector where emission factors incorporate information on firewood and local operation conditions. However, as mentioned above, differences in CO2 emissions between both inventories also points to biases in the quantification of the activity. This inventory (available at https://doi.org/10.5281/zenodo.4784286) (Alamos et al., 2021)) will support the design of policies that seek to mitigate climate change and improve air quality by providing policy makers, stakeholders and scientists with qualified scientific spatial explicit emission information.

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Section: Residential Sectormentioning

confidence: 99%

Section: Comparison Of Total Emissions By Sector and Pollutant With Edgar Inventorymentioning

confidence: 99%

Section: Uncertainty and Quality Of Estimations On The Residential Sectormentioning

confidence: 99%

See 1 more Smart Citation

High resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential sectors of Chile

Álamos

Huneeus

Opazo

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Even if not originally found in the biofuel composition, PAHs and PCDD/PCDF can be formed during combustion of coal, 63 biomass, 64,65 and other organic matter. 66 PCDD and PCDF are produced when C, H, Cl, and O are present together with a copper catalyst.…”

Section: Emissions Of Volatile Organic Compounds Polycyclic Aromatic Hydrocarbons Dioxins and Furansmentioning

confidence: 99%

Gaseous emissions from co‐combustion of biosolids from the meat processing industry with wood

Virmond

Albrecht²,

Althoff³

et al. 2021

Env Prog and Sustain Energy

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Flotation sludge from the meat processing industry can be applied as biofuel in already existing plant-scale boilers. This biosolid is rich in oil and grease and has higher energetic content on a dry ash-free basis (22.74 and 27.71 MJ kg −1 ) than the wood-based fuel (16.62 and 16.16 MJ kg −1 ). Co-combustion trials were performed at a pilot-scale cyclonic combustor (100 kg h −1 ) and at an industrial flamotubular rotatory grate-fired system (6000 kg h −1 ), co-firing pre-dried and centrifuged flotation sludges (respectively) and wood at a mass ratio of 1:3. At a moisture content of 60.13 wt%, the lower heating value of the centrifuged sludge was 10.24% lower compared to wood, thus reducing it to at least 40 wt% would be advisable to obtain energy gains in the industrial plant when operating the co-combustion. The emissions were evaluated and compared to emission standards, including the characterization of polycyclic aromatic hydrocarbons and polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (given as Toxicity Equivalent Factors at O 2ref = 7%), which have not yet been reported. The 16 target polycyclic aromatic hydrocarbons were identified at pilot and plant scales (0.582 ± 0.143 μg Nm −3 and 0.602 ± 0.506 μg Nm −3 , respectively) being lower than the Danish reference standard (5.0 μg Nm −3 ). The polychlorinated dibenzop-dioxins and polychlorinated dibenzofurans concentrations were 0.0004 ± 0.0001 ng Nm −3 at pilot scale and 0.3617 ± 0.1310 ng Nm −3 at plant scale, both below the Brazilian and American standards but differed greatly between the scales, requiring further investigation since their formation can occur due to combustion and postcombustion conditions.

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Section: Comparison Of Total Emissions By Sector and Pollutant With Edgar Inventorymentioning

Effects of wood moisture on emission factors for PM2.5, particle numbers and particulate-phase PAHs from Eucalyptus globulus combustion using a controlled combustion chamber for emissions

Cited by 29 publications

References 53 publications

High resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential sectors of Chile

High resolution inventory of atmospheric emissions from transport, industrial, energy, mining and residential sectors of Chile

Gaseous emissions from co‐combustion of biosolids from the meat processing industry with wood

Comment on essd-2021-216

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