Quantification of Global Primary Emissions of PM_2.5, PM₁₀, and TSP from Combustion and Industrial Process Sources

Abstract

Emission quantification of primary particulate matter (PM) is essential for assessment of its related climate and health impacts. To reduce uncertainty associated with global emissions of PM2.5, PM10, and TSP, we compiled data with high spatial (0.1° × 0.1°) and sectorial (77 primary sources) resolutions for 2007 based on a newly released global fuel data product (PKU-FUEL-2007) and an emission factor database. Our estimates for developing countries are higher than those previously reported. Spatial bias associated with large countries could be reduced by using subnational fuel consumption data. Additionally, we looked at temporal trends from 1960 to 2009 at country-scale resolution. Although total emissions are still increasing in developing countries, their intensities in terms of gross domestic production or energy consumption have decreased. PM emitted in developed countries is finer owing to a larger contribution from nonindustrial sources and use of abatement technologies. In contrast, countries like China, with strong industry emissions and limited abatement facilities, emit coarser PM. The health impacts of PM are intensified in hotspots and cities owing to covariance of sources and receptors. Although urbanization reduces the per person emission, overall health impacts related to these emissions are heightened because of aggregation effects.

Scale- and Region-Dependence in Landscape-PM2.5 Correlation: Implications for Urban Planning

“…The correlation coefficient of SHDI and AI reach maximum at a distance of 4000 m to the in situ site, while those of F_PLAND and C1_PLAND reach the maximum at a distance of 5000 m. This suggests that the neighboring land use regulation has a potential influence on local PM 2.5 concentration. Correlation with F_PLAND and C1_PLAND are consistent with most previous studies, which revealed that forest could help to improve the air quality, while the urbanization could worsen the pollution [20][21][22][25][26][27]. The new finding of this study refers to the negative correlation of SHDI and positive correlation of AI in the Jing-Jin-Ji region.…”

Globalization and pollution: tele-connecting local primary PM 2.5 emissions to global consumption

“…agriculture, industrial activity, power generation, transportation and non-transportation services). This classification is different from what has been used in previous studies that divide PM 2.5 emissions into four categories: industrial, power, transportation and residential [15,64,65]. This study focuses on primary industrial emissions and primary residential emissions that amount to 24 and 15.6 Tg, respectively.…”

“…Notably, the pattern of consumption-based emission for PM 2.5 is different from that of CO 2 , which the consumption-based CO 2 emission has been widely studied by previous literature. Based on global production-based emission inventory [15] and MRIO table derived from GTAP database [66], China's consumption-based PM 2.5 emissions is found to more than four times the USA's in 2007, whereas China's consumption-based CO 2 emissions amounted to only 61% of those of the USA in the same year [2]. This difference stemmed from the larger difference in emission factor, sectoral emission intensity and substantial residential emissions across regions.…”

“…In this framework, we first conducted a production-based PM 2.5 emission inventory ( F Pr ) using 134 countries/regions (electronic supplementary material, table S1) and 57 industry sectors (electronic supplementary material, table S2) on the basis of previous studies [15,54]. Thereafter, by allocating the direct and indirect PM 2.5 emissions to final consumer demand, we derived a global consumption-based PM 2.5 emission inventory for 2007.…”

“…Energy consumption by sector, GDP and population data of each region were all derived from the GTAP database. Further details to the development of PKU-PM-2007 and comparison with other inventories can be found in our previous studies [15,54,63]. …”