Dynamics of pollutant emissions from wildfires in Mainland China

We analyzed the dynamics of pollutant emissions from wildfires in mainland China from 2001 to 2019 using MODIS fire products combined with the measurements of emission factors of different vegetation types. The biomass distribution in Mainland China has heterogeneous temporal and spatial pattern, with inter-year variations and a decreasing trend from east to west. Overall, from 2001 to 2019, biomass combustion in Mainland China reached 479.59 Tg (25.24 Tg·a-1), in which northeast, north, east, south, central, northwest, and southwest regions accounted for 20.95%, 31.14%, 8.89%, 9.06%, 3.98%, 0.33% and 25.64% of total biomass combustion, respectively. The emissions of CO, CO₂, CxHy, NOx, PM_2.5, TC, OC and EC were 47.30, 288.05, 12.90, 0.40, 1.43, 0.83, 0.70, and 0.12 Tg (1 Tg = 10¹²g), respectively. PM_2.5, TC and OC emissions increased in the southwest, while all pollutant emissions declined significantly in the southern region. For particulate matter from wildfires, both the ratio of its emissions to total dust and the ratio of its concentration to atmospheric PM_2.5 showed an increasing trend, implying that the relative environmental impacts of particulate emissions from wildfires may be rising. In addition, our results show that the current Chinese wildfire management has successfully reduced on average more than 80% of pollutant emissions from wildfire from 2001 to 2019 compared to the natural wildfire regime (no strict wildfire management). This research on the temporal-spatial changes of pollutant emissions from wildfires in Mainland China provides support for further exploration of wildfire impacts on regional environments, and indicates the effectiveness of Chinese current wildfire policy on the pollutant emission mitigation.

An extensive dust storm impact on air quality on 22 November 2018 in Sydney, Australia, using satellite remote sensing and ground data

Recurrent dust storms represent a significant concern in Australia because of their related hazards and damages since particulate matter (PM) has harmful impacts on the environmental, health and economic sectors. The particulate matter may be released from natural sources and human activities. The major part of natural particulate matter is emitted into the air by wind erosion processes from desert and semi-desert areas at the world scale. A huge dust storm crossed over several areas of New South Wales (NSW), Australia, including the Sydney region on 21-22 November 2018 and decreased the horizontal visibility to less than 1 km for 22 h. This study examined the synoptic weather conditions, and assessed the air quality and identified the source and transport trajectory of the dust storm over Sydney using ground and satellite remote sensing data. PM10 (< 10 μm) concentrations were obtained from selected air quality monitoring sites operated by the Environmental Protection Agency in NSW. The highest hourly concentration of PM10 (578.7 μg/m³) was recorded at Singleton in the Hunter Valley, while concentrations in Sydney ranged from 480 to 385 μg/m³, well above the standard air quality level in Australia (50 μg/m³ per 24 h). The HYSPLIT back trajectories of air parcels suggest that the potential sources of the dust episode originated from the Lake Eyre Basin and northeast South Australia, the Mundi Mundi plains west of Broken Hill, Cobar and the grazing lands and the red sandplains in northwestern NSW. It then travelled towards the east coast. These long-range airflows transported suspended dust particles, raising air quality to hazardous levels (elevated PM10 levels) over most areas of NSW. The results from the HYSPLIT model for dust movement are confirmed by MODIS satellite images. Many areas of NSW experienced this intense dust storm due to northwest wind generated by the low-pressure systems and cold fronts over South Australia and many parts of western NSW as it moved eastward.

Remote sensing approach for the estimation of particulate organic carbon in coastal waters based on suspended particulate concentration and particle median size

The particulate organic carbon (POC) content retrieved by remote sensors is influenced by the suspended particulate concentration (SPC) and the particle size distribution (PSD). The objective of this study was to provide study case of remote sensing monitoring of non-optical activity substance POC in Hangzhou bay, China. A modified empirical remote sensing algorithm was established based on SPC and median particle size (D₅₀) to describe the influence of PSD variation on remote sensing reflectance (R_rs). The algorithm was applied to MODIS data to reveal POC spatial and temporal variations. The results show that the accuracy of the remote sensing estimation algorithm, established on the basis of Mie theory, is relatively higher than the empirical model simply based on the statistical correlation between R_rs and POC. The POC in Hangzhou bay caused by spring and neap tides vary significantly.

Satellite data regarding the eutrophication response to human activities in the plateau lake Dianchi in China from 1974 to 2009

Human activities contribute highly to water eutrophication. In this study, the relationship between human activities and water eutrophication in Dianchi Lake in China was characterized using a combination of satellite imaging, sedimentary physicochemical and meteorological data analyses. The heavy eutrophic status and algal bloom in Dianchi Lake were first observed by satellite in 1977 and 1989, respectively. The C/N ratio, an indicator of organic sources in sediments, also showed that the planktonic organic source in the sediment significantly increased beginning in 1989. The land use cover in the Dianchi basin showed that both farm lands and forests, but particularly farmlands, were reduced during the period from 1974 to 2009. The urbanized land area increased from 1974 to 2009, particularly after 2000. The effects of human activities on water eutrophication were expressed by land use cover, population, gross domestic product (GDP; separated into primary, secondary and tertiary industries) and wastewater discharge. For land use cover, farm and urbanized lands were the main sources of water nutrients; forest contributed slightly to these nutrients. For GDP, primary (correlation coefficient=0.94, P<0.001) and tertiary (correlation coefficient=0.95, P<0.001) industries were highly correlated with total nitrogen. Secondary (correlation coefficient=0.95, P<0.001) and tertiary (correlation coefficient=0.96, P<0.001) industries were highly correlated with total phosphorus. The algal bloom area was significantly correlated with wastewater discharge (correlation coefficient=0.78, P<0.005) (except industrial wastewater), which was primarily led by the non-agricultural population, from 2000 to 2009. This study suggests that the protection of water environments requires a comprehensive protection policy in addition to a unilateral protection policy.