The carbonaceous aerosol is one of the important components of the aerosol and plays a significant role in changing climate, fluctuating air quality and health of the living being. These carbonaceous aerosols emitted by the partial burning of fossil fuels through several processes such as emissions from industries, traffic and biomass burning including domestic heating. The carbonaceous aerosol is separated in elemental carbon and organic carbon. The optical determination methods of carbonaceous aerosol classify the refractory carbon as black carbon (BC) and light-absorbing carbonaceous aerosols as brown carbon (BrC). BrC includes a huge and variable assemblage of organic compounds. BrC is a refractory aerosol from the thermo-chemical point of view and never evaporates up to 400°C under inert atmospheric condition. Brown carbon has high absorbance in the blue and ultraviolet (UV) region of the solar spectrum. Recently, brown carbon attracted the interest of researchers due to its role in climate change. The brown carbon produced by the partial burning of hydrocarbons/tar material (smoldering) and sunlight-induced oxidation of biogenic material. In this book chapter, authors provide a detailed review of source characterization, geographical distribution, chemistry and possible environmental and climate impacts of brown carbon.

A large concern with estimates of climate and health co-benefits of "clean" cookstoves from controlled emissions testing is whether results represent what actually happens in real homes during normal use. A growing body of evidence indicates that in-field emissions during daily cooking activities differ substantially from values obtained in laboratories, with correspondingly different estimates of co-benefits. We report PM2.5 emission factors from uncontrolled cooking (n = 7) and minimally controlled cooking tests (n = 51) using traditional chulha and angithi stoves in village kitchens in Haryana, India. Minimally controlled cooking tests (n = 13) in a village kitchen with mixed dung and brushwood fuels were representative of uncontrolled field tests for fine particulate matter (PM2.5), organic and elemental carbon (p > 0.5), but were substantially higher than previously published water boiling tests using dung or wood. When the fraction of nonrenewable biomass harvesting, elemental, and organic particulate emissions and modeled estimates of secondary organic aerosol (SOA) are included in 100 year global warming commitments (GWC100), the chulha had a net cooling impact using mixed fuels typical of the region. Correlation between PM2.5 emission factors and GWC (R2 = 0.99) implies these stoves are climate neutral for primary PM2.5 emissions of 8.8 ± 0.7 and 9.8 ± 0.9 g PM2.5/kg dry fuel for GWC20 and GWC100, respectively, which is close to the mean for biomass stoves in global emission inventories.

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2.5 and O3) using state-of-the-science emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. 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, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2.5 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. Comparisons between observed and simulated O3 and PM2.5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions. Observed and predicted ozone levels over New Delhi during September 2015, December 2015, and September 2016 routinely exceeded the 8 h Indian standard of 100 µg m−3, and, on occasion, exceeded 180 µg m−3. PM2.5 levels are predicted over the SOMAARTH headquarters (September 2015 and September 2016), Bajada Pahari (a village in the surveillance site; September 2015, December 2015, and September 2016), and New Delhi (September 2015, December 2015, and September 2016). The predicted fractional impact of residential emissions on anthropogenic PM2.5 levels varies from about 0.27 in SOMAARTH HQ and Bajada Pahari to about 0.10 in New Delhi. The predicted secondary organic portion of PM2.5 produced by household emissions ranges from 16 % to 80 %. Predicted levels of secondary organic PM2.5 during the periods studied at the four locations averaged about 30 µg m−3, representing approximately 30 % and 20 % of total PM2.5 levels in the rural and urban stations, respectively.

The contribution of firework-related air pollutants into the rural atmosphere was monitored by measuring ambient air concentrations of PM2.5, CO, and metals over Mitrol– Aurangabad, Haryana, India, before, during, and after the 2015 Diwali celebration. PM2.5 concentrations were observed to be approximately 5 times and 12 times higher than Indian and WHO 24-h standards, respectively. CO concentrations on the day of Diwali were found to be nearly 7.5 times and nearly 1.5 times higher than Indian standards and WHO 8-h standards, respectively. Increased concentrations of SO4, K, N3, Al, and Na were observed. SO4, K, N3, Al, and Na were found between approximately 2 and 5 times higher on festival days than on a normal, non-festival day in November. Use of firecrackers during Diwali and surrounding celebrations thus contribute to decreased air quality and elevated levels of air pollutants associated with adverse health impacts. Optimization or controlled use of firecrackers during Diwali is suggested in rural areas.

Air quality in rural India is impacted by residential cooking and heating with biomass fuels. In this study, emissions of CO, CO2, and 76 volatile organic compounds (VOCs) and fine particulate matter (PM2.5) were quantified to better understand the relationship between cook fire emissions and ambient ozone and secondary organic aerosol (SOA) formation. Cooking was carried out by a local cook, and traditional dishes were prepared on locally built chulha or angithi cookstoves using brushwood or dung fuels. Cook fire emissions were collected throughout the cooking event in a Kynar bag (VOCs) and on polytetrafluoroethylene (PTFE) filters (PM2.5). Gas samples were transferred from a Kynar bag to previously evacuated stainless-steel canisters and analyzed using gas chromatography coupled to flame ionization, electron capture, and mass spectrometry detectors. VOC emission factors were calculated from the measured mixing ratios using the carbon-balance method, which assumes that all carbon in the fuel is converted to CO2, CO, VOCs, and PM2.5 when the fuel is burned. Filter samples were weighed to calculate PM2.5 emission factors. Dung fuels and angithi cookstoves resulted in significantly higher emissions of most VOCs (p < 0.05). Utilizing dung–angithi cook fires resulted in twice as much of the measured VOCs compared to dung–chulha and 4 times as much as brushwood–chulha, with 84.0, 43.2, and 17.2 g measured VOC kg−1 fuel carbon, respectively. This matches expectations, as the use of dung fuels and angithi cookstoves results in lower modified combustion efficiencies compared to brushwood fuels and chulha cookstoves. Alkynes and benzene were exceptions and had significantly higher emissions when cooking using a chulha as opposed to an angithi with dung fuel (for example, benzene emission factors were 3.18 g kg−1 fuel carbon for dung–chulha and 2.38 g kg−1 fuel carbon for dung–angithi). This study estimated that 3 times as much SOA and ozone in the maximum incremental reactivity (MIR) regime may be produced from dung–chulha as opposed to brushwood–chulha cook fires. Aromatic compounds dominated as SOA precursors from all types of cook fires, but benzene was responsible for the majority of SOA formation potential from all chulha cook fire VOCs, while substituted aromatics were more important for dung–angithi. Future studies should investigate benzene exposures from different stove and fuel combinations and model SOA formation from cook fire VOCs to verify public health and air quality impacts from cook fires.

Exposure to harmful by-products of combustion arising from the use of biomass fuels for cooking and heating in rural areas of developing countries results in poor air quality and is responsible for millions of deaths yearly. Little formal quantification and measurement of carbon monoxide (CO), one of these harmful air pollutants, have been performed in rural areas of North India. In the current study, we measured exposure to CO from cooking and heating in seven households using biomass and liquid petroleum gas (LPG) in open and closed kitchens. Exposures to CO ranged from 4.81 to 7.01, 0.20 to 1.81, and 0.02 to 0.75 mg m−3 for households cooking with biomass, cooking with LPG, and for households in which no cooking occurred, respectively. It was observed that the CO concentration in biomass-only households is much higher (78%) than in LPG-only households (14%). We found exposures in closed kitchens approximately two times higher than in open kitchens. Location of the kitchen (i.e., open vs. closed) was the most important determinant of exposure of primary cooks to CO in this geography.

Emissions of airborne particles from biomass burning are a significant source of black carbon (BC) and brown carbon (BrC) in rural areas of developing countries where biomass is the predominant energy source for cooking and heating. This study explores the molecular composition of organic aerosols from household cooking emissions with a focus on identifying fuel-specific compounds and BrC chromophores. Traditional meals were prepared by a local cook with dung and brushwood-fueled cookstoves in a village in Palwal district, Haryana, India. Cooking was done in a village kitchen while controlling for variables including stove type, fuel moisture, and meal. Fine particulate matter (PM2.5) emissions were collected on filters, and then analyzed via nanospray desorption electrospray ionization–high-resolution mass spectrometry (nano-DESI-HRMS) and high-performance liquid chromatography–photodiode array–high-resolution mass spectrometry (HPLC-PDA-HRMS) techniques. The nano-DESI-HRMS analysis provided an inventory of numerous compounds present in the particle phase. Although several compounds observed in this study have been previously characterized using gas chromatography methods a majority of the species in the nano-DESI spectra were newly observed biomass burning compounds. Both the stove (chulha or angithi) and the fuel (brushwood or dung) affected the composition of organic aerosols. The geometric mean of the PM2.5 emission factor and the observed molecular complexity increased in the following order: brushwood–chulha (7.3 ± 1.8 g kg−1 dry fuel, 93 compounds), dung–chulha (21.1 ± 4.2 g kg−1 dry fuel, 212 compounds), and dung–angithi (29.8 ± 11.5 g kg−1 dry fuel, 262 compounds). The mass-normalized absorption coefficient (MACbulk) for the organic-solvent extractable material for brushwood PM2.5 was 3.7 ± 1.5 and 1.9 ± 0.8 m2 g−1 at 360 and 405 nm, respectively, which was approximately a factor of two higher than that for dung PM2.5. The HPLC-PDA-HRMS analysis showed that, regardless of fuel type, the main chromophores were CxHyOz lignin fragments. The main chromophores accounting for the higher MACbulk values of brushwood PM2.5 were C8H10O3 (tentatively assigned to syringol), nitrophenols C8H9NO4, and C10H10O3 (tentatively assigned to methoxycinnamic acid).

Natural and human activities generate a significant amount of PM2.5 (particles ≤2.5 μm in aerodynamic diameter) into the surrounding atmospheric environments. Because of their small size, they can remain suspended for a relatively longer time in the air than coarse particles and thus can travel long distances in the atmosphere. PM2.5 is one of the key indicators of pollution and known to cause numerous types of respiratory and lung-related diseases. Due to poor implementation of regulations and a time lag in introducing the vehicle technology, levels of PM2.5 in most Asian cities are much worse than those in European environments. Dedicated reviews on understanding the characteristics of PM2.5 in Asian urban environments are currently missing but much needed. In order to fill the existing gaps in the literature, the aim of this review article is to describe dominating sources and their classification, followed by current status and health impact of PM2.5, in Asian countries. Further objectives include a critical synthesis of the topics such as secondary and tertiary aerosol formation, chemical composition, monitoring and modelling methods, source apportionment, emissions and exposure impacts. The review concludes with the synthesis of regulatory guidelines and future perspectives for PM2.5 in Asian countries. A critical synthesis of literature suggests a lack of exposure and monitoring studies to inform personal exposure in the household and rural areas of Asian environments.

Introduction: Exposure to household air pollution from solid fuel use for cooking results in approximately 925,000 deaths yearly in India. A significant portion of emissions of harmful air pollutants resulting from cooking impacts ambient air quality. As part of ongoing work in North India, we concurrently measured PM2.5 at different scales to better understand the relationships between stove usage, personal exposure, and ambient air pollution. Methods: We deployed Met One E-Samplers with a sharp-cut cyclone to measure both integrated and real-time PM2.5 at a central and peripheral site of Bajada Pahadi, a village of approximately 100 households in Palwal District, Haryana, India located away from roads, industrial sources, and other villages. Cooking in the village occurs predominantly outdoors throughout the year. We concurrently measured stove usage of all solid fuel using devices in 35 homes and performed two weeks of intensive 24-hour personal exposure assessment in the same homes. In a small number of households, we measured 24-hour PM2.5 exposures with no cooking and separately with LPG-only cooking. Results: Our findings indicate high average concentrations of ambient PM2.5 during winter months, with a mean daily concentration of approximately 255 µg/m3 (range 105 – 495 µg/m3) in December and January. Ambient concentrations and village-wide primary traditional stove use both peak between 5 and 8a and between 5 and 7p. A simple linear model with no covariates indicates a linear relationship between ambient concentrations and stove use, with an R2 of 0.42. Analysis of relationships between stove usage and near-home concentrations and personal exposures is ongoing. Conclusions: Ambient air pollution in North India appears to be influenced by traditional stove usage. Average levels of ambient air pollution were well above Indian standards and WHO guidelines, suggesting a need for monitoring in rural areas, where approximately 68% of the population resides.

Measurement of the moisture content of biomass fuels is critical for the measurement of emission factors and accounting for differences in stove performance results from standardized tests such as the water boiling test. Moisture probe measurements have been used systematically for the assessment of moisture content of woody fuels, as it is more convenient than laboratory-based oven-drying methods because multiple measurements can be rapidly performed on-site as the fuel for the cooking task is selected for use. Current protocols, however, state that the probes used to measure moisture content in wood cannot be used with dung, crop residues, or other non-wood fuels. The averages from 5 replicate moisture probe measurements on each of 35 cow and buffalo dung patties from Haryana, India, were compared to oven drying moisture measurement at 103±2°C. Dung patties were selected ranging in moisture content from 5% to 65% on a dry basis based on probe measurements with 5 unique patties in each 10% increment. The results showed good linearity between moisture probe ≤55% and oven drying methods (r2=0.76). Results were then used to adjust uncontrolled measurements of dung moisture taken prior to cooking for 17 homes in 4 villages in rural Haryana, India, which demonstrate that the commonly used moisture probe, when calibrated against oven-based methods, can be used to assess moisture content of dung patties over the range of dung moisture typically found and used in villages for cooking purposes.