10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Linking PM2.5 Indoor Air Quality and Emission Factors Measured during a Cookstove Intervention Trial in Rural India
MOHAMMAD MAKSIMUL ISLAM, Roshan Wathore, Grishma Jain, Karthik Sethuraman, Hisham Zerriffi, Julian Marshall, Rob Bailis, Andrew Grieshop, North Carolina State University
Abstract Number: 1391 Working Group: Indoor Aerosols
Abstract Combustion of biomass in residential cookstoves is a major source of household air pollution (HAP), an acknowledged threat to human health. Although there are many studies showing the effect of biomass cookstove on HAP, there are limited number of studies where both emission and indoor air quality were measured across different seasons and at different locations. Thus, the quantitative linkage between cookstove emission and indoor air quality is still poorly constrained. In this study, we assess the effect of a cookstove intervention trial on indoor PM2.5 concentration as well as its seasonality and inter-site variability in two rural areas in India (Kullu in Himanchal Pradesh; Koppal in Karnataka). This study also aims to improve our ability to quantify the link between cookstove emissions and indoor PM2.5.
The study had three ~3-month-long measurement periods (baseline, follow-up-1, follow-up-2) for each location. Indoor PM2.5 concentrations were measured during ~5000 cooking events of traditional and alternate biomass and modern-fuel stoves. Measurements were conducted with real time mobile instruments (RTI micro-PEMS) which include a nephelometer and collect filter samples for gravimetric PM2.5 analysis. For a subset of those cooking events, simultaneous emission measurements were conducted by a portable instrument (STEMS). Kitchen performance tests (KPT) were performed to assess daily household fuel use. Use of stoves was measured using temperature-logging stove use monitors (SUMs) installed on all cooking appliances.
Preliminary data analysis for baseline showed that median indoor 24 hour average PM2.5 concentration in households in Kullu having Himansu Tandoor (improved chimney heating stove) as primary stove was 72 µg/m³, approximately a factor of two lower than for those with Traditional Tandoor stoves (142 µg/m³). A similar trend was observed during follow-up-1 (267 and 138 µg/m³ for Traditional and Himansu Tandoor respectively), indicating reduced pollution was associated with improved chimney stoves. Indoor PM2.5 for both stoves during follow-up-1 were twice as high as baseline, consistent with strong seasonality in PM2.5 concentrations. The households in Kullu and Koppal having LPG (either as primary or secondary stove) had median PM2.5 concentrations of 91 and 111 µg/m³ respectively, about 1.5-2 times less than households having no LPG stoves (142 and 207 µg/m³ in Kullu and Koppal respectively). The median PM2.5 concentration for houses having primarily traditional stoves was higher for Koppal (206 µg/m³) than Kullu (132 µg/m³), strong evidence of inter-site variability in PM2.5 concentration.
Stove-influenced (SI) periods were identified in the real time PM2.5 data using an algorithm and decay phase of SI periods were used to calculate air exchange rates (AER). Higher AER in Kullu households (11±5 h-1) compared to Koppal (7±4 h-1) may explain the reduced PM2.5 concentration in Kullu for the same stove. Average stove-influenced PM2.5 concentrations were higher during follow-up-1 (1127 and 1045 µg/m³ in Koppal and Kullu, respectively) than non-stove-influenced concentrations (45 and 26 µg/m³ in Koppal and Kullu, respectively). Moreover, stove-influenced PM2.5 concentrations were positively correlated (r2=0.89 & 0.79 for Koppal and r2=0.68 & 0.62 for Kullu during baseline and follow-up-1, respectively) with indoor daily average PM2.5 concentrations, indicating as expected, a strong association between cookstove emissions and indoor PM2.5. PM2.5 emission rate will be calculated using PM2.5 emission factor from emission measurement and fuel consumption rate from KPT. SUMs data will be used to identify cooking events associated with each stove types, and PM2.5 concentrations corresponding to those events will be obtained from SI analysis. Finally, with the help of AER and ventilation characteristics from household surveys, a statistical model will be developed linking emissions rate and indoor PM2.5 air quality.