Associations between Ozone and Morbidity Using the Spatial Synoptic Classification System

Abstract Background Synoptic circulation patterns (large-scale tropospheric motion systems) affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses) on the association between ozone and hospital admissions for asthma and myocardial infarction (MI) among adults in North Carolina. Methods Daily surface meteorology data (including precipitation, wind speed, and dew point) for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS), which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions. Results Ozone was associated with asthma under dry tropical (1- to 5-day lags), transitional (3- and 4-day lags), and extreme moist tropical (0-day lag) air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag) air masses. Conclusions Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain synoptic circulation patterns/air masses in conjunction with ambient ozone levels were associated with increased asthma and MI hospitalizations

Cardiovascular Outcomes and the Physical and Chemical Properties of Metal Ions Found in Particulate Matter Air Pollution: a QICAR Study

Background: This paper presents an application of quantitative ion character–activity relationships (QICAR) to estimate associations of human cardiovascular (CV) diseases (CVDs) with a set of metal ion properties commonly observed in ambient air pollutants. QICAR has previously been used to predict ecotoxicity of inorganic metal ions based on ion properties

Effects of Agricultural Biomass Burning on Regional Haze in China: A Review

Burning agricultural straw before and/or after harvest is a common farming practice. Regional and extensive agricultural open field straw burning can cause serious air pollution events. This paper looks at the effects of biomass burning emission on regional haze that should be considered in the forecasting of regional haze. It describes the current state of crop residue burning in China, and analyzes the relationship between biomass burning and regional haze in terms of temporal/spatial patterns and chemical composition. Finally, some suggestions/recommendations are proposed for the recycling of agricultural straw to reduce the impact of biomass burning on regional haze and air quality. We suggest that prescribed open burning would be a more suitable solution in China. We hope that this report about biomass burning and regional haze will bring the issue to the attention of governments and other researchers

Estimates of Dust Emissions and Organic Carbon Losses Induced by Wind Erosion in Farmland Worldwide from 2017 to 2021

Wind erosion can cause high dust emissions from agricultural land and can lead to a significant loss of carbon and nutrients from the soil. The carbon balance of farmland soil is an integral part of the carbon cycle, especially under the current drive to develop carbon-neutral practices. However, the amount of global carbon lost due to the wind erosion of farmland is unknown. In this study, global farmland dust emissions were estimated from a dust emission inventory (0.1° × 0.1°, daily) built using the improved Community Multiscale Air Quality Modeling System–FENGSHA (CMAQ-FENGSHA), and global farmland organic carbon losses were estimated by combining this with global soil organic carbon concentration data. The average global annual dust emissions from agricultural land from 2017 to 2021 were 1.75 × 109 g/s. Global dust emissions from agricultural land are concentrated in the UK, Ukraine, and Russia in Europe; in southern Canada and the central US in North America; in the area around Buenos Aires, the capital of Argentina, in South America; and in northeast China in Asia. The global average annual organic carbon loss from agricultural land was 2970 Gg for 2017–2021. The spatial distribution of emissions is roughly consistent with that of dust emissions, which are mainly concentrated in the world’s four major black soil regions. These estimates of dust and organic carbon losses from agricultural land are essential references that can inform the global responses to the carbon cycle, dust emissions, and black soil conservation

Spatiotemporal Distribution of Satellite-Retrieved Ground-Level PM2.5 and Near Real-Time Daily Retrieval Algorithm Development in Sichuan Basin, China

Satellite-based monitoring can retrieve ground-level PM2.5 concentrations with higher-resolution and continuous spatial coverage to assist in making management strategies and estimating health exposures. The Sichuan Basin has a complex terrain and several city clusters that differ from other regions in China: it has an enclosed air basin with a unique planetary boundary layer dynamic which accumulates air pollution. The spatiotemporal distribution of 1-km resolution Aerosol Optical Depth (AOD) in the Sichuan Basin was retrieved using the improved dark pixel method and Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The retrieved seasonal AOD reached its highest values in spring and had the lowest values in autumn. The higher correlation (r = 0.84, N = 171) between the ground-based Lidar AOD and 1-km resolution MODIS AOD indicated that the high-resolution MODIS AOD could be used to retrieve the ground-level PM2.5 concentration. The Lidar-measured annual average extinction coefficient increased linearly with the Planetary Boundary Layer Height (PBLH) in the range of 100~670 m, but exponentially decreased between the heights of 670~1800 m. Both the correlation and the variation tendency of simulated PBLH from the Weather Research and Forecasting (WRF) model & Shin-Hong (SHIN)/California Meteorological (CALMET) model (WRF_SHIN/CALMET) were closer to the Lidar observation than that of three other Planetary Boundary Layer (PBL) schemes (the Grenier-Bretherton-McCaa (GBM) scheme, the Total Energy-Mass Flux (TEMF) scheme and the University of Washington (UW) scheme), which suggested that the simulated the Planetary Boundary Layer Height (PBLH) could be used in the vertical correction of retrieval PM2.5. Four seasonal fitting functions were also obtained for further humidity correction. The correlation coefficient between the aerosol extinction coefficient and the fitted surface-level PM2.5 concentration at the benchmark station of Southwest Jiao-tong University was enhanced significantly from 0.62 to 0.76 after vertical and humidity corrections during a whole year. During the evaluation of the retrieved ground-level PM2.5 with observed values from three cities, Yibin (YB), Dazhou (DZ), and Deyang (DY), our algorithm performed well, resulting in higher correlation coefficients of 0.78 (N = 177), 0.77 (N = 178), and 0.81 (N = 181), respectively

Interannual and Seasonal Variability of Greenhouse Gases and Aerosol Emissions from Biomass Burning in Northeastern China Constrained by Satellite Observations

Biomass burning is a major source of greenhouse gases (GHGs) and particulate matter (PM) emissions in China. Despite increasing efforts of fire monitoring, it remains challenging to quantify the variability in interannual and seasonal emissions of GHGs and PM from biomass burning. In this study, we investigated the biomass burning emissions in Northeastern China based on fire radiative power (FRP) obtained from the Visible Infrared Imaging Radiometer Suites (VIIRS) active fires datasets during the period 2012 to 2019. Our results showed that the average annual emissions from biomass burning in Northeastern China during 2012–2019 were: 81.6 Tg for CO2, 260.2 Gg for CH4, 5.5 Gg for N2O, 543.2 Gg for PM2.5 and 573.6 Gg for PM10, respectively. Higher levels of GHGs and PM emissions were concentrated in the Songnen Plain and Sanjiang Plain, the main grain producing areas in this region, and were associated with dense fire points. There were two emission peaks observed each year: after harvesting (October to November) and before planting (March to April). During this study period, the total fire emissions initially increased and then decreased in a fluctuating pattern, with emissions peaking in 2015, the year when more emission regulations were introduced. Crop straw was the major source of GHGs and PM among all kinds of biomass burning. Following more stringent controls on burning and the utilization of crop straw, the main burning season changed from autumn to spring. The proportion from spring burning increased from 20.5% in 2013 to 77.1% in 2019, with an annual growth rate of 20%. The results of this study demonstrate the effectiveness of regulatory control in reducing GHGs and PM emissions, as well as satellite fire observations as a powerful means to assess such outcomes

Interannual and Seasonal Variability of Greenhouse Gases and Aerosol Emissions from Biomass Burning in Northeastern China Constrained by Satellite Observations

Biomass burning is a major source of greenhouse gases (GHGs) and particulate matter (PM) emissions in China. Despite increasing efforts of fire monitoring, it remains challenging to quantify the variability in interannual and seasonal emissions of GHGs and PM from biomass burning. In this study, we investigated the biomass burning emissions in Northeastern China based on fire radiative power (FRP) obtained from the Visible Infrared Imaging Radiometer Suites (VIIRS) active fires datasets during the period 2012 to 2019. Our results showed that the average annual emissions from biomass burning in Northeastern China during 2012–2019 were: 81.6 Tg for CO2, 260.2 Gg for CH4, 5.5 Gg for N2O, 543.2 Gg for PM2.5 and 573.6 Gg for PM10, respectively. Higher levels of GHGs and PM emissions were concentrated in the Songnen Plain and Sanjiang Plain, the main grain producing areas in this region, and were associated with dense fire points. There were two emission peaks observed each year: after harvesting (October to November) and before planting (March to April). During this study period, the total fire emissions initially increased and then decreased in a fluctuating pattern, with emissions peaking in 2015, the year when more emission regulations were introduced. Crop straw was the major source of GHGs and PM among all kinds of biomass burning. Following more stringent controls on burning and the utilization of crop straw, the main burning season changed from autumn to spring. The proportion from spring burning increased from 20.5% in 2013 to 77.1% in 2019, with an annual growth rate of 20%. The results of this study demonstrate the effectiveness of regulatory control in reducing GHGs and PM emissions, as well as satellite fire observations as a powerful means to assess such outcomes

Simulating Performance of CHIMERE on a Late Autumnal Dust Storm over Northern China

The accurate forecasting of dust emission and transport is a societal demand worldwide as dust pollution is part of many health, economic, and environment issues, which significantly impact sustainable development. The dust forecasting ability of present air quality forecast systems is mainly focused on spring dust events in East Asia, but further improvement may be needed as there is still difficulty in forecasting autumn dust activities, such as failing to predict the serious dust storm that occurred on 25 to 26 November 2018. In this study, a state-of-the-art air quality model, CHIMERE, with three coupled dust schemes was introduced for the first time to simulate the dust emissions during this event to qualitatively and quantitatively validate its dust simulating performance over Northern China. The model results reported that two of the three dust schemes were able to capture the dust emission source located in Gansu Province and reproduce the easterly dust transport path, showing moderately close agreement in the horizontal and vertical distribution patterns with the ground-based and satellite observations. The simulated PM10 concentration had a better relationship with the observed values with a correlation coefficient up to 0.96, while it was lower in the transported areas. Meanwhile, the simulations also presented incorrect dust emission positions such as in areas between the Hulun Buir sandy land and Horqin sandy land. Our results indicate that CHIMERE exhibits reasonably good performance regarding its dust simulation and forecast ability over this area, and its application would help to improve the dust analysis and forecast abilities in Northern China

Review on physicochemical properties of pollutants released from fireworks: environmental and health effects and preventions

The pollutants released from fireworks may seriously deteriorate air quality and adversely impact on human health. In order to aid in obtaining comprehensive observations and in the establishment of effective legislation aimed at controlling the short-term effects of fireworks, we systematically reviewed the findings of previous studies of the impacts of fireworks. These studies, primarily located in Asia (more than 70% studies), Europe and North America, considered particle concentrations, size distribution, morphology, noise and chemical composition (including water-soluble ions, elements, carbonaceous material, organic matter and trace gases), along with the associated human health effects during fireworks display. 41% studies suggested that the concentrations of firework particles were reported to be 1 - 5 times higher than the respective background values. And the mean ratios PM10/TSP, PM2.5/PM10 and PM1.0/PM2.5 were 0.64, 0.72 and 0.65, respectively. During festivals, the concentrations of SO42- and K+ were the highest of the water-soluble ions. For major elements and gaseous pollutants, K, S and CO, SO2 had the highest concentrations, respectively. The health effects of particles and gaseous pollutants, including metals, emitted from fireworks need further epidemiological study to aid in the prevention of health problems and the treatment of patients. Fireworks industries should technical innovation to reduce pollutants emissions. Emissions inventories of fireworks display should be compiled and used in Eulerian models, to forecast the spatiotemporal distribution of pollutants and to further assistant the government in establishing appropriate restriction levels and legislation which balance environmental protection and festive spirit.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author