Guannan Geng

Transboundary health impacts of transported global air pollution and international trade

Millions of people die every year from diseases caused by exposure to outdoor air pollution. Some studies have estimated premature mortality related to local sources of air pollution, but local air quality can also be affected by atmospheric transport of pollution from distant sources. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region. The effects of international trade on air pollutant emissions, air quality and health have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM2.5) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM2.5 pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM2.5 pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM2.5 pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.

Revealing the Hidden Health Costs Embodied in Chinese Exports

China emits a considerable amount of air pollutants when producing goods for export. Previous efforts have emphasized the magnitude of export-related emissions; however, their health consequences on the Chinese population have not been quantified. Here, we present an interdisciplinary study to estimate the health impact of export-related air pollution. The results show that export-related emissions elevated the annual mean population weighted PM2.5 by 8.3 μg/m(3) (15% of the total) in 2007, causing 157,000 deaths and accounting for 12% of the total mortality attributable to PM2.5-related air pollution. Compared to the eastern coastal provinces, the inner regions experience much larger export-related health losses relative to their economic production gains, owing to huge inter-regional disparities in export structures and technology levels. A shift away from emission-intensive production structure and export patterns, especially in inner regions, could significantly help improve national exports while alleviating the inter-regional cost-benefit inequality. Our results provide the first quantification of health consequences from air pollution related to Chinese exports. The proposed policy recommendations, based on health burden, economic production gains, and emission analysis, would be helpful to develop more sustainable and effective national and regional export strategies.

Fusing Observational, Satellite Remote Sensing and Air Quality Model Simulated Data to Estimate Spatiotemporal Variations of PM2.5 Exposure in China

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. Through assembling techniques, including linear mixed effect regressions with a spatial-varying coefficient, a maximum likelihood estimator and the spatiotemporal Kriging together, we develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1° over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.0 μg/m3 and R2 = 0.72) and outperforms either AOD-derived PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-derived PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides spatiotemporally complete predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.7 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81 across China during 2014. Fused estimates will be publicly available for future health-related studies.

Chemical composition of ambient PM 2. 5 over China and relationship to precursor emissions during 2005–2012

In this work, we presented the characteristics of PM2.5 chemical composition over China for the period of 2005–2012 by synthesis of in situ measurement data collected from literatures and satellite-based estimates using aerosol optical depth (AOD) data and the GEOS-Chem chemical transport model. We revealed the spatiotemporal variations in PM2.5 composition during 2005–2012 and investigated the driving forces behind the variations by examining the changes in precursor emissions using a bottom-up emission inventory. Both in situ observations and satellitebased estimates identified that secondary inorganic aerosols (i.e., sulfate, nitrate, and ammonium; SNA) ranked as the highest fraction of dust-free PM2.5 concentrations, followed by organic matter (OM) and black carbon (BC). For instance, satellite-based estimates found that SNA, OM, and BC contributed to 59, 33, and 8 %, respectively, of national population-weighted mean dust-free PM2.5 concentrations during 2005–2012. National population-weighted mean PM2.5 concentration increased from 63.9 μg m−3 in 2005 to 75.2 μg m−3 in 2007 and subsequently decreased to 66.9 μg m−3 from 2007 to 2012. Variations in PM2.5 concentrations are mainly driven by the decrease in sulfate and the increase in nitrate. Population-weighted mean sulfate concentration decreased by 2.4 % yr−1 during 2005–2012 (from 14.4 to 12.9 μg m−3), while population-weighted mean nitrate concentration increased by 3.4 % yr−1 during 2005– 2012 (from 9.8 to 12.2 μg m−3), largely offsetting the decrease in sulfate concentrations. By examining the emission data from the Multi-resolution Emission Inventory for China (MEIC), we found that the changes in sulfate and nitrate concentrations were in line with the decrease in SO2 emissions and the increase in NOx emissions during the same period. The desulfurization regulation in power plants enforced around 2005 has been the primary contributor to the SO2 emission reduction since 2006. In contrast, growth of energy consumption and lack of control measures for NOx resulted in a persistent increase in NOx emissions until the installation of denitrification devices on power plants late in 2011, which began to take effect in 2012. The results of this work indicate that the synchronized abatement of emissions for multipollutants is necessary for reducing ambient PM2.5 concentrations over China.