Disease burden and health risk to rural communities of northeastern India from indoor cooking-related exposure to parent, oxygenated and alkylated PAHs.

Exposure to a total of 51 targeted and non-targeted polycyclic aromatic hydrocarbons (PAHs) and their oxygenated and alkylated derivatives associated with size-segregated aerosol was investigated in rural kitchens using liquefied petroleum gas (LPG), mixed biomass (MB) and firewood (FW) fuels in northeastern India. The averaged PM10-associated parent-, alkylated-, and oxygenated-PAHs concentrations increased notably from LPG (257, 54, and 116 ng m-3) to MB (838, 119, and 272 ng m-3) to FW-using kitchens (2762, 225, and 554 ng m-3), respectively. PAHs were preferentially associated with the PM1 fraction with contributions increasing from 80 % in LPG to 86 % in MB and 90 % in FW-using kitchens, which in turn was dominated by <0.25 µm particles (54-75 % of the total). A clear profile of enrichment of low-molecular weight PAHs in cleaner fuels (LPG) and a contrasting enrichment of high-molecular weight PAHs in biomass-based fuels was noted. The averaged internal dose of Benzo[a]pyrene equivalent was the lowest in the case of LPG (19 ng m-3), followed by MB (161 ng m-3) and the highest in FW users (782 ng m-3). Estimation of incremental lifetime cancer risk (ILCR) from PAH exposure revealed extremely high cancer risk in biomass users (factors of 8-40) compared to LPG. The potential years of life lost (PYLL) and PYLL rate averaged across kitchen categories was higher for lung cancer (PYLL: 10.55 ± 1.04 years; PYLL rate: 204 ± 426) compared to upper respiratory tract cancer (PYLL: 10.02 ± 0.05 years; PYLL rate: 4 ± 7), and the PYLL rates for biomass users were higher by factors of 9-56 as compared to LPG users. These findings stress the need for accelerated governmental intervention to ensure a quick transition from traditional biomass-based fuels to cleaner alternatives for the rural population of northeastern India.

Understanding population exposure to size-segregated aerosol and associated trace elements during residential cooking in northeastern India: Implications for disease burden and health risk.

Mass-size distribution of respirable aerosol and 13 associated trace elements (TEs) were investigated in rural kitchens using liquefied petroleum gas (LPG), firewood and mixed biomass fuels across three northeastern Indian states. The averaged PM10 (particulate matter with aerodynamic diameter ≤ 10 µm) and ΣTE concentrations were 403 and 30 µg m-3 for LPG, 2429 and 55 µg m-3 for firewood, and 1024 and 44 µg m-3 for mixed biomass-using kitchens. Mass-size distributions were tri-modal with peaks in the ultrafine (0.05-0.08 µm), accumulation (0.20-1.05 µm), and coarse (3.20-4.57 µm) modes. Respiratory deposition, estimated using the multiple path particle dosimetry model, ranged from 21 % to 58 % of the total concentration across fuel types and population age categories. Head, followed by pulmonary and tracheobronchial, was the most vulnerable deposition region, and children were the most susceptible age group. Inhalation risk assessment of TEs revealed significant non-carcinogenic as well as carcinogenic risk, especially for biomass fuel users. The potential years of life lost (PYLL) was the highest for chronic obstructive pulmonary disease (COPD: 15.9 ± 3.8 years) followed by lung cancer (10.3 ± 0.3 years) and pneumonia (10.1 ± 0.1 years), while the PYLL rate was also highest for COPD, with Cr(VI) being the major contributor. Overall, these findings reveal the significant health burden faced by the northeastern Indian population from indoor cooking using solid biomass fuels.

Elemental composition of rural household dust in Brahmaputra fluvial plain: insights from SEM-EDS, receptor model, and risk assessment.

The study attempts to look into the morphological characteristics, elemental composition, contamination, source contributions, and associated health risks in household dust of Napaam, a rural region in the Brahmaputra flood plain in North East India. Morphological evidence suggests that most of the house dust particles were sourced from vehicle abrasion and soil. Three contamination indices-enrichment factor (EF), index of geo-accumulation (Igeo), and pollution load index (PLI) indicated that Cl and four trace elements (Cu, Zn, As, and Pb) are significantly enriched in house dust with extreme pollution load. Principal component analysis (PCA) and positive matrix factorization (PMF) revealed 3 potential major sources of elements in house dust-traffic + re-suspension of road dust (35.8%), soil dust (22.2%), and river sediment deposit (16.4%). Two minor sources-biomass burning (13.3%), and construction activities (12.3%) were also identified. Based on health risk assessment (HRA), both children and adult were found to be susceptible to non-carcinogenic and carcinogenic risks.

Effects of Protected Area Size on Conservation Return on Investment.

The objective of this research is to examine how protected area size influences the conservation benefit and acquisition cost of creating a protected area, how the resulting effects influence the predicted rate of return on investment (ROI), and how those relationships change prioritization decision-making for selecting protected areas compared with decisions based only on conservation benefit and decisions based only on acquisition cost. The objective is accomplished in an econometric framework by analyzing the parcel-level acquisition cost and conservation benefit measured by the change in potential fragmentation patterns on the landscape resulting from protection. We focus on areas acquired by The Nature Conservancy in central and southern Appalachia, United States. As an indicator of the change in landscape fragmentation, we use a fragmentation statistic known as effective mesh size. Although the effect of protected parcel size on predicted ROI is inelastic, greater conservation effectiveness is obtained with larger protected parcels than with smaller ones on average. Protected parcel size influences parcels' rankings for protection more (less) when only the predicted change in effective mesh size of protected area (only the predicted acquisition cost per area) is used for prioritizing parcels than when the ranking of parcels is determined by the predicted ROI. These findings imply that, although protected parcel size is important, failure to prioritize using ROI could result in an inappropriate level of emphasis being given to protected parcel size than is warranted.