Puji Lestari

Size distribution and dry deposition of particulate mass, sulfate and nitrate in an urban area

Abstract Atmospheric size distributions for mass, sulfate and nitrate were measured in Chicago, Illinois during the Spring–Summer, and Fall of 1994 and 1995. Nineteen samples were collected over two or three daytime periods using a Wide Range Aerosol Classifier system (Noll Rotary Impactor and Cascade Impactor). The Atmospheric Aerosol was divided into 10 size range between 0.1 and 100xa0μm. The total particulate mass contains three peaks, a fine peak (mode) with an MMD of 0.43xa0μm, and two coarse particulate peaks at 6.75 (mode 2) and 28.58xa0μm (mode 3). The total concentration of particles and the location of the concentration peaks varied significantly depending on wind velocity. Data shows that sulfate and nitrate existed in both the fine ( 2.5xa0μm) particles. The atmospheric concentration of sulfate in the fine and coarse particles varied between 1.0–7.0 and 0.3–1.0xa0μg/m3, respectively. The nitrate concentrations were 0.3–5.3xa0μg/m3 in the fine and 0.3–2.9xa0μg/m3 in the coarse fraction. Dry deposition fluxes were simultaneously measured with a knife edged surrogate surface containing greased mylar films. The measured dry deposition fluxes of sulfate and nitrate were between 1.0–4.0 and 0.5–3.9xa0mg/(m2xa0day), respectively. A multi-step method was used to calculate total and cumulative deposition flux with the Semhel–Hodgson deposition velocity model and atmospheric particulate concentration. The results indicated that calculated flux compares well with measured flux, and greater than 99% of the total flux was due to particles larger than 5xa0μm diameter for both sulfate and nitrate. The average ratios of calculated/measured fluxes were 0.93 for sulfate and 0.91 for nitrate.

Characteristics of carbonaceous aerosols emitted from peatland fire in Riau, Sumatra, Indonesia (2): Identification of organic compounds

Abstract Smoke emitted from Indonesian peatland fires has caused dense haze and serious air pollution in Southeast Asia such as visibility impairment and adverse health impacts. To mitigate the Indonesian peatland fire aerosol impacts, an effective strategy and international framework based on the latest scientific knowledge needs to be established. Although several attempts have been made, limited data exist regarding the chemical characteristics of peatland fire smoke for the source apportionment. In order to identify the key organic compounds of peatland fire aerosols, we conducted intensive field studies based on ground-based and source-dominated sampling of PM 2.5 in Riau Province, Sumatra, Indonesia, during the peatland fire seasons in 2012. Levoglucosan was the most abundant compound among the quantified organic compounds at 8.98xa0±xa02.28% of the PM 2.5 mass, followed by palmitic acid at 0.782xa0±xa00.163% and mannosan at 0.607xa0±xa00.0861%. Potassium ion was not appropriate for an indicator of Indonesian peatland fires due to extremely low concentrations associated with smoldering fire at low temperatures. The vanillic/syringic acids ratio was 1.06xa0±xa00.155 in this study and this may be a useful signature profile for peatland fire emissions. Particulate n -alkanes also have potential for markers to identify impact of Indonesian peatland fire source at a receptor site.

Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model

Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m3), mineral dust (1.9-14.7 μg/m3), residual/organic matter (2.1-40.2 μg/m3), and black carbon (1.0-7.3 μg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m3), industry (6.5 μg/m3), and power generation (5.6 μg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM2.5 provides insight into sources and processes that influence the global spatial variation in PM2.5 composition.

A quantitative assessment of distributions and sources of tropospheric halocarbons measured in Singapore

This work reports the first ground-based atmospheric measurements of 26 halocarbons in Singapore, an urban-industrial city-state in Southeast (SE) Asia. A total of 166 whole air canister samples collected during two intensive 7 Southeast Asian Studies (7SEAS) campaigns (August-October 2011 and 2012) were analyzed for C1-C2 halocarbons using gas chromatography-electron capture/mass spectrometric detection. The halocarbon dataset was supplemented with measurements of selected non-methane hydrocarbons (NMHCs), C1-C5 alkyl nitrates, sulfur gases and carbon monoxide to better understand sources and atmospheric processes. The median observed atmospheric mixing ratios of CFCs, halons, CCl4 and CH3CCl3 were close to global tropospheric background levels, with enhancements in the 1-17% range. This provided the first measurement evidence from SE Asia of the effectiveness of Montreal Protocol and related national-scale regulations instituted in the 1990s to phase-out ozone depleting substances (ODS). First- and second-generation CFC replacements (HCFCs and HFCs) dominated the atmospheric halocarbon burden with HFC-134a, HCFC-22 and HCFC-141b exhibiting enhancements of 39-67%. By combining near-source measurements in Indonesia with receptor data in Singapore, regionally transported peat-forest burning smoke was found to impact levels of several NMHCs (ethane, ethyne, benzene, and propane) and short-lived halocarbons (CH3I, CH3Cl, and CH3Br) in a subset of the receptor samples. The strong signatures of these species near peat-forest fires were potentially affected by atmospheric dilution/mixing during transport and by mixing with substantial urban/regional backgrounds at the receptor. Quantitative source apportionment was carried out using positive matrix factorization (PMF), which identified industrial emissions related to refrigeration, foam blowing, and solvent use in chemical, pharmaceutical and electronics industries as the major source of halocarbons (34%) in Singapore. This was followed by marine and terrestrial biogenic activity (28%), residual levels of ODS from pre-Montreal Protocol operations (16%), seasonal incidences of peat-forest smoke (13%), and fumigation related to quarantine and pre-shipment (QPS) applications (7%).

Modeling Indoor PM 2.5 Air Pollution, Estimating Exposure, and Problems Associated with Rural Indonesian Households Using Wood Fuel

A large segment of rural Indonesian households still use wood as their main fuel for cooking. In this study, we modeled the indoor air pollution implications and estimated exposures using PM2.5 concentrations in kitchens and living rooms with time activity information by season at villages in West Java Province (Lembang, highland) and in Central Java Province (Juwana, coastal area). The PM2.5 concentrations were measured 24 h using UCB particle monitors. Modeling indoor air pollution was conducted using a single box model. The average daily exposures in Lembang and Juwana were 0.24 (mg/m3) and 0.1 (mg/m3), respectively. The relative risks (RRs) (95% CI) of cardiopulmonary diseases due to wood fuel use were, respectively, 1.52 and 1.44 for Lembang and Juwana. The adjusted RRs for cardiovascular diseases were, respectively, 1.47 and 1.39 for Lembang and Juwana. The ratio of simulated concentrations to actual concentrations was better for the Lembang site, 0.9 and 1.7, compared to the Juwana site, 1.13 and 1.8, for the wet and dry seasons, respectively. Overall, this model is quite useful to preliminarily assess the indoor air pollution that might occur if housing parameters are well characterized. It seems that this model has greater accuracy for predicting moderate indoor kitchen concentrations, i.e., those around 1 mg/m3. Adoption of dual fuel energy (LPG-wood fuel) in rural areas is mainly driven by economical motive. To solve the problem comprehensively, it needs long-term, medium-term, and short-term program. The immediate action (short term-program) is to mitigate indoor air pollution within rural households as much as possible by ventilation arrangement and good cooking practice implementation.

Woodfuel Utilization for Cooking in Indonesian Household: Assessment of Indoor PM10 Pollution and Wood Consumption at National Level

After national fuel switching was launched in mid-2007 across Indonesia, people in rural area seem to have dual fuels (wood and LPG) for daily cooking. Field measurements of indoor air pollution related to cooking activities were accomplished in 40 households at two sites (Lembang and Juwana) of Indonesian rural areas during December 2010 to January 2011. Size segregated PM10 indoor aerosols related to cooking emission were quantified with a Sioutas Cascade impactor. The average PM10 concentrations related to the stoves emissions were 1,209 ± 918 μg/m3 in Lembang and 1,375 ± 884 μg/m3 in Juwana. Averages of 3.3 ± 1.6 kg and 3.8 ± 1.9 kg wood were consumed daily for Lembang site and Juwana site respectively. The PM1 contributed to 86% and 88% of PM10 mass concentration at Lembang and Juwana respectively. While the PM2.5 shared 90% and 92% of PM10 mass concentration at Lembang and Juwana respectively. Additionally, combination of measured unit consumption of woodfuel with the previous data on woodfuel consumption allowed national household consumption for cooking by island in Indonesia. The total consumption was estimated to be 106 million m3/year and Java island accounted for the largest share of 31%.