Dataset Information

Health Impact of PM₁₀, PM_2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

ABSTRACT: The most important anthropogenic sources of primary particulate matter (PM) in ambient air in Europe are exhaust and non-exhaust emissions from road traffic and combustion of solid biomass. There is convincing evidence that PM, almost regardless of source, has detrimental health effects. An important issue in health impact assessments is what metric, indicator and exposure-response function to use for different types of PM. The aim of this study is to describe sectorial contributions to PM exposure and related premature mortality for three Swedish cities: Gothenburg, Stockholm and Umea. Exposure is calculated with high spatial resolution using atmospheric dispersion models. Attributed premature mortality is calculated separately for the main local sources and the contribution from long-range transport (LRT), applying different relative risks. In general, the main part of the exposure is due to LRT, while for black carbon, the local sources are equally or more important. The major part of the premature deaths is in our assessment related to local emissions, with road traffic and residential wood combustion having the largest impact. This emphasizes the importance to resolve within-city concentration gradients when assessing exposure. It also implies that control actions on local PM emissions have a strong potential in abatement strategies.

SUBMITTER: Segersson D

PROVIDER: S-EPMC5551180 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Health Impact of PM<sub>10</sub>, PM<sub>2.5</sub> and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

Segersson David D Eneroth Kristina K Gidhagen Lars L Johansson Christer C Omstedt Gunnar G Nylén Anders Engström AE Forsberg Bertil B

International journal of environmental research and public health 20170707 7

The most important anthropogenic sources of primary particulate matter (PM) in ambient air in Europe are exhaust and non-exhaust emissions from road traffic and combustion of solid biomass. There is convincing evidence that PM, almost regardless of source, has detrimental health effects. An important issue in health impact assessments is what metric, indicator and exposure-response function to use for different types of PM. The aim of this study is to describe sectorial contributions to PM expos ...[more]

PMID: 28686215

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Project description:Rapid urbanization and consuming lifestyles have intensified air pollution in urban areas. Air pollution in megacities has imposed severe environmental damages to human health. Proper management of the issue necessitates identification of the share of emission sources. Therefore, numerous research works have studied the apportionment of the total emissions and observed concentrations among different emissions sources. In this research, a comprehensive review is conducted to compare the source apportioning results for ambient air PM2.5 in the megacity of Tehran, the capital of Iran. One hundred seventy-seven pieces of scientific literatures, published between 2005 and 2021, were reviewed. The reviewed research are categorized according to the source apportioning methods: emission inventory (EI), source apportionment (SA), and sensitivity analysis of the concentration to the emission sources (SNA). The possible reasons for inconsistency among the results are discussed according to the scope of the studies and the implemented methods. Although 85% of the reviewed original estimates identify that mobile sources contribute to more thant 60% of Tehran air pollution, the distribution of vehicle types and modes are clearly inconsistent among the EI studies. Our review suggests that consistent results in the SA studies in different locations in central Tehran may indicate the reliability of this method for the identification of the type and share of the emission sources. In contrast, differences among the geographical and sectoral coverage of the EI studies and the disparities among the emission factors and activity data have caused significant deviations among the reviewed EI studies. Also, it is shown that the results of the SNA studies are highly dependent on the categorization type, model capabilities and EI presumptions and data input to the pollutant dispersion modelings. As a result, integrated source apportioning in which the three methods complement each other's results is necessary for consistent air pollution management in megacities.Supplementary informationThe online version contains supplementary material available at 10.1007/s40201-023-00855-0.

Project description:India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 μg m-3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.

Project description:ObjectiveTo compare estimates of spatiotemporal variations of surface PM2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM2.5 annual mean at municipality level.MethodsWe retrieved PM2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM2.5 concentration over the current mean annual national standard of 25 µg/m3 and projected standard of 15 µg/m3.ResultsCompared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m3 compared to a mean bias of 4,7 µg/m3 from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM2.5 exposure over 25 and 15 µg/m3 were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m3 were 2,381 years.ConclusionComparison of two global air quality models for estimating surface PM2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

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Dataset Information

Health Impact of PM₁₀, PM_2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

Publications

Health Impact of PM<sub>10</sub>, PM<sub>2.5</sub> and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

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Dataset Information

Health Impact of PM10, PM2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

Publications

Health Impact of PM<sub>10</sub>, PM<sub>2.5</sub> and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Health Impact of PM₁₀, PM_2.5 and Black Carbon Exposure Due to Different Source Sectors in Stockholm, Gothenburg and Umea, Sweden.