Environmental Controls to Soil Heavy Metal Pollution Vary at Multiple Scales in a Highly Urbanizing Region in Southern China.

Natural and anthropogenic activities affect soil heavy metal pollution at different spatial scales. Quantifying the spatial variability of soil pollution and its driving forces at different scales is essential for pollution mitigation opportunities. This study applied a multivariate factorial kriging technique to investigate the spatial variability of soil heavy metal pollution and its relationship with environmental factors at multiple scales in a highly urbanized area of Guangzhou, South China. We collected 318 topsoil samples and used five types of environmental factors for the attribution analysis. By factorial kriging, we decomposed the total variance of soil pollution into a nugget effect, a short-range (3 km) variance and a long-range (12 km) variance. The distribution of patches with a high soil pollution level was scattered in the eastern and northwestern parts of the study domain at a short-range scale, while they were more clustered at a long-range scale. The correlations between the soil pollution and environmental factors were either enhanced or counteracted across the three distinct scales. The predictors of soil heavy metal pollution changed from the soil physiochemical properties to anthropogenic dominated factors with the studied scale increase. Our study results suggest that the soil physiochemical properties were a good proxy to soil pollution across the scales. Improving the soil physiochemical properties such as increasing the soil organic matter is essentially effective across scales while restoring vegetation around pollutant sources as a nature-based solution at a large scale would be beneficial for alleviating local soil pollution.

A meteorologically adjusted ensemble Kalman filter approach for inversing daily emissions: A case study in the Pearl River Delta, China.

The conventional Ensemble Kalman filter (EnKF), which is now widely used to calibrate emission inventories and to improve air quality simulations, is susceptible to simulation errors of meteorological inputs, making accurate updates of high temporal-resolution emission inventories challenging. In this study, we developed a novel meteorologically adjusted inversion method (MAEInv) based on the EnKF to improve daily emission estimations. The new method combines sensitivity analysis and bias correction to alleviate the inversion biases caused by errors of meteorological inputs. For demonstration, we used the MAEInv to inverse daily carbon monoxide (CO) emissions in the Pearl River Delta (PRD) region, China. In the case study, 60% of the total CO simulation biases were associated with sensitive meteorological inputs, which would lead to the overestimation of daily variations of posterior emissions. Using the new inversion method, daily variations of emissions shrank dramatically, with the percentage change decreased by 30%. Also, the total amount of posterior CO emissions estimated by the MAEInv decreased by 14%, indicating that posterior CO emissions might be overestimated using the conventional EnKF. Model evaluations using independent observations revealed that daily CO emissions estimated by MAEInv better reproduce the magnitude and temporal patterns of ambient CO concentration, with a higher correlation coefficient (R, +37.0%) and lower normalized mean bias (NMB, -17.9%). Since errors of meteorological inputs are major sources of simulation biases for both low-reactive and reactive pollutants, the MAEInv is also applicable to improve the daily emission inversions of reactive pollutants.

Near-real-time estimation of hourly open biomass burning emissions in China using multiple satellite retrievals.

Open biomass burning (OBB) is an important source of air pollutants and greenhouse gases, but its dynamic emission estimation remains challenging. Existing OBB emission datasets normally provide daily estimates based upon Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals but tend to underestimate the emissions due to the coarse spatial resolution and sparse observation frequency. In this study, we proposed a novel approach to improve OBB emission estimations by fusing multiple active fires detected by MODIS, Visible Infrared Imaging Radiometer onboard the Suomi National Polar-orbiting Partnership (VIIRS S-NPP) and Himawari-8. The fusion of multiple active fires can capture the missing small fires and the large fires take place during the non-overpass time of MODIS observations. Also, regional-based fire radiative power (FRP) cycle reconstruction models and OBB emission coefficients were developed to address the large spatial discrepancies of OBB emission estimations across China and to promote the estimate to an hourly resolution. Using the new approach, hourly gridded OBB emissions in China were developed and can be updated with a lag of 1-day, or even near-real-time when real-time multiple active fires are available. OBB emissions in China based on this approach were more than 3 times of those in previous datasets. Evaluations revealed that the spatial distribution of the estimated PM2.5 emissions from this study was more consistent with the ambient PM2.5 concentrations during several episodes than existing datasets. The hourly OBB emissions provide new insight into its spatiotemporal variations, enhance timely and reliable air quality modeling and forecast, and support the formulation of accurate prevention and control policies of OBB.

A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China.

Volatile organic compounds (VOCs) source profiles can be used for a number of purposes, such as creating speciated air pollutant emission inventories and providing inputs to receptor and air quality models. In this study, we first collected and schematically evaluated more than 500 Chinese domestic source profiles from literature and field measurements, and then established a most up-to-date dataset of VOCs source profiles in China by integrating 363 selective VOCs profiles into 101 sector-based source profiles. The profile dataset covers eight major source categories and contains 447 VOCs species including non-methane hydrocarbons (NMHCs) species and oxygenated VOCs (OVOCs) species. The results shown that (1) VOCs composition characteristics exhibit variations for most Level-II source sectors and Level-III sub-sectors even under the same Level-I source category; (2) OVOCs, which were significantly missing in previous profiles, account for more than 95% in cooking and 20- 40% in non-road mobile, biomass burning and solvent use sources; (3) aromatics account for 20%-40% in most emission sources except cooking source, alkenes and alkynes account for ~20% in combustion sources (stationary combustion, mobile source and biomass burning), alkanes are abundant in gasoline-related emission sources(on-road mobile source and fuel oil storage and transportation); (4) missing OVOCs species could bring 30%-50% to ozone formation potentials in most emission sources; and (5) there are considerable differences in VOCs chemical groups and individual species for most emission sources between this dataset and the widely used U.S. SPECIATE database, indicating the importance of developing domestic VOCs source profiles. The dataset developed in this study can help support reactive VOCs species-based ozone control strategy and provide domestic profile data for source apportionment and air quality modeling in China and other countries or regions with similar emission source characteristics.

Insight into the characteristics of carbonaceous aerosols at urban and regional sites in the downwind area of Pearl River Delta region, China.

Carbonaceous aerosols (CAs) take up a substantial fraction of fine particle (PM2.5) in the atmosphere, yet high temporal resolution and seasonal variations of their emission sources and formation mechanisms are still poorly characterized in the regions with strong anthropogenic activities. In this study, the spatiotemporal characteristics of CAs and their subfractions, i.e., organic carbon (OC) and elemental carbon (EC), were studied in one of China's key city clusters, the Pearl River Delta (PRD) region. Results show that the annual mean OC and EC concentrations are 5.89 ± 3.32 µg/m3 and 1.60 ± 1.00 µg/m3 at the urban site, respectively. Such levels are consistently higher than those at the regional site (4.94 ± 3.34 µg/m3 of OC and 1.45 ± 0.82 µg/m3 of EC), suggesting the strong impact of human activities on OC and EC concentration. Moreover, the OC concentration peak sharply appears at 19:00 across all seasons at the urban site due to the direct influence of traffic exhaust and cooking activities. At regional site, OC peaks in fall afternoon due to intensive photochemical reactions derived combustion-related secondary organic carbon (SOCcom) contributions to the downwind PRD region. Correlations between SOCcom and influence factors were found at both regional and urban sites, suggesting that SOCcom formation is more regionally homogenous and mainly originates from the Zhaoqing-Foshan-Jiangmen belt. In addition, there are significantly different formation mechanisms of non-combustion-related secondary organic carbon (SOCnon-com) in the downwind PRD region. This study provides a solid evidence for collaborative efforts in the mitigation of secondary aerosols in the PRD region.

Role of export industries on ozone pollution and its precursors in China.

This study seeks to estimate how global supply chain relocates emissions of tropospheric ozone precursors and its impacts in shaping ozone formation. Here we show that goods produced in China for foreign markets lead to an increase of domestic non-methane volatile organic compounds (NMVOCs) emissions by 3.5 million tons in 2013; about 13% of the national total or, equivalent to half of emissions from European Union. Production for export increases concentration of NMVOCs (including some carcinogenic species) and peak ozone levels by 20-30% and 6-15% respectively, in the coastal areas. It contributes to an estimated 16,889 (3,839-30,663, 95% CI) premature deaths annually combining the effects of NMVOCs and ozone, but could be reduced by nearly 40% by closing the technology gap between China and EU. Export demand also alters the emission ratios between NMVOCs and nitrogen oxides and hence the ozone chemistry in the east and south coast.

Regional discrepancies in spatiotemporal variations and driving forces of open crop residue burning emissions in China.

As a major source of secondary organic aerosol, open crop residue burning (OCB) emits a large number of trace gases and particulates to the atmosphere. Extensive OCB is detected during harvest seasons in most regions of China. Emissions from OCB have been widely investigated in China, but few studies have focused on regional discrepancies in spatiotemporal variations with a long timescale. In this study, emissions from OCB in three typical regions of China, including Northeast China, Chengdu-Chongqing and Guangdong, from 2003 to 2016, were estimated using a combination of statistical data and the Moderate Resolution Imaging Spectroradiometer (MODIS) observations, and regional discrepancies in spatiotemporal variations and driving forces were analyzed in detail. The results showed that OCB emissions of CO and PM2.5 in 2016 were 3.63 × 106 and 6.96 × 105 tons in Northeast China, 9.77 × 105 and 1.36 × 105 tons in Chengdu-Chongqing, and 1.24 × 105 and 1.19 × 104 tons in Guangdong, respectively. The OCB emissions in Northeast China maintained an overall increasing trend, which were mainly dominated by rural economic development and agricultural modernization, with great potential for reduction. In Chengdu-Chongqing, emissions increased until 2013 and then decreased, due to the impact of policies prohibiting OCB. In Guangdong, emissions showed annual fluctuations with a slightly decreasing trend influenced by metrological conditions and related policies. The analysis of the driving forces behind the regional discrepancies among these typical regions indicated that OCB emissions in China were characterized by uneven rural economic development, control policies, and natural conditions, suggesting that region-dependent control measures are needed for reducing OCB emissions. This study provided a better understanding of OCB emission characteristics in the three typical regions and revealed the diversity of OCB emission characteristics in China.

Anthropogenic atmospheric toxic metals emission inventory and its spatial characteristics in Guangdong province, China.

Atmospheric toxic metals (TMs) may cause adverse effects on the environment and human health due to their bioavailability and toxicity. High-resolution TMs emission inventory is important input data for assessing human exposure risks, especially synergistic toxicity of multiple toxic metals. By using the latest city- and enterprise-level environment statistical data, an emission inventory of five TMs (Hg, As, Pb, Cd, Cr) in Guangdong province for the year of 2014 was developed using a bottom-up approach. The total emissions of Hg, As, Pb, Cd and Cr in Guangdong were estimated as 17.70, 32.59, 411.34, 13.13, and 84.16 t, respectively. Major emission sources for each TM were different. Hg emissions were dominated by coal combustion (33%), fluorescent lamp (18%) and cement (17%). 78% of Hg emissions were in the form of Hg0, 19% of Hg2+, and only 3% of Hgp due to strict particulate matter control policies. Coal combustion (48%), nonferrous metal smelting (25%) and iron and steel industry (24%) were the major sources of As. Pb emissions primarily came from battery production (42%), iron and steel industry (21%) and gasoline combustion (17%). Cd and Cr emissions were dominated by nonferrous metal smelting (71%) and iron and steel industry (82%), respectively. Most of these TMs were emitted in the non-Pearl River Delta region, where the newly-built iron and steel industry, nonferrous metal smelting and cement production factories were intense. The uncertainties in the five TM emissions were high, due much to high uncertainties in TM emission factors and limited activity data. Thus, to improve the accuracy of these estimates, we recommend more field tests of TM emissions, especially for the industrial process sector. This study provides scientific support for formulating robust TMs control policies to alleviate the high risk of TMs exposure in Guangdong.

Recent developments of anthropogenic air pollutant emission inventories in Guangdong province, China.

Emission inventory (EI) requires continuous updating to improve its quality and reduce its uncertainty. In this study, recent developments on source classification, emission methods, emission factors and spatial-temporal surrogates in the Guangdong regional anthropogenic emission inventory are presented. The developments include: ~40 additional emission sources in a re-classified source classification system, >50 improved spatial and temporal surrogates, 85% of local/domestic emission factors used, and updated estimation methods of on-road mobile, marine, and solvent use sources. The developments were updated to the recent 2012-based high resolution emission inventories, and their results were compared with previous 2006- and 2010-based emission inventories. The results indicated: (1) The total SO2, NOx, CO, PM10, PM2.5, BC, OC, VOCs and NH3 emissions in 2012 were 777.0kt, 1532.2kt, 7305.4kt, 1176.4kt, 480.9kt, 54.2kt, 79.9kt, 1255.1kt and 584.1kt, respectively, for Guangdong province, with higher emission densities observed in the central PRD region. (2) No great changes on source structures were found among three years, but their contributions varied. (3) SO2, PM10 and PM2.5 emissions showed downward trends, likely a result of strict control measures on power plant and industrial combustion sources. (4) NOx emission exhibited relatively stable levels in 2010 and 2012, but contributions from industrial, on-road and non-road mobile sources increased. (5) VOCs emissions showed an upward trend, mainly resulting from dramatically increased light-duty passenger car population and solvent use. (6) Spatial and temporal allocations were updated with constant improvements of spatial and temporal surrogates. (7) Uncertainty ranges of emission estimates were reduced, indicating that the 2012-based PRD regional EI are more reliable. The work shown in this study can be a reference example for other regions to continuously update their emission inventories.

[Research on spectral reflectance characteristics for Glycyrrhizae Radix].

In order to study the spectral reflectance differences of Glycyrrhizae Radix under different growth conditions and lay the foundation for quantitative monitoring of Glycyrrhizae Radix remote sensing images, spectra of Glycyrrhiza species under different growth period and different varieties and different regions were measured by a portable spectrometer. The results showed that the reflectivity of annual G. uralensis was obviously higher than that of the two years plant in the visible light band own to the contents of crown layer chlorophyll. The reflectivity of two years G. pallidiflora was higher than that of G. uralensis in the near infrared band own to the leaf area index and the content of leaf water. The red edge spectrum of annual plant fluctuated largely than that of two years plant due to vegetation coverage and leaf area index. G. pallidiflora grew well than G. uralensis. Under different regions of the Glycyrrhiza species, spectral data analysis showed that within a certain range, the average annual precipitation and average annual evaporation were the major factors to affect the differences of Glycyrrhiza species spectral data under different regions owe to the leaf water content, the higher leaf water content, the lower spectral reflectance. The principal component analysis and continuum-removed method of the spectral data under different regions found that, within a certain range, the average annual precipitation and average annual evaporation were the major factors caused by the differences of Glycyrrhiza species spectral data under the different regions, Glycyrrhiza species spectral similarity related to the spatial distance.

[Quality variation and ecotype division of Panax quinquefolium in China].

Quality variation and ecotype classification of Chinese herbal medicine are important scientific problems in Daodi herbal medicine research. The diversity of natural environmental conditions has led to form unique multi-Daodi, multi-product areas that produce particular Chinese herbal medicine. China is one of three big American ginseng (Panax quinquefolium L.) producing areas worldwide, with over 300 years of application and 40 years of cultivation history. Long-term production practice has led to the formation of three big advocate produce areas in China: Northeast province, Beijing and Shandong. P. quinquefolium L. grown under certain environmental conditions will develop long-term adaptations that will lead to more stable strains (different ecotypes). P. quinquefolium L., can vary greatly in quality; however, the ecological mechanisms causing this variation are still unclear. Root samples were collected from four-year-old cultivated P. quinquefolium L. plants in the three major genuine (Daodi) American ginseng-producing areas of Northeast province, Beijing and Shandong province, China. Ultra-performance liquid chromatography was used to analyze the contents of eight ginsenosides (Rg1, Re, Rb1, Rb2, Rb3, Rc, Rd, Rg2). Data for nine ecological factors, including temperature, moisture and sunlight, were obtained from the ecological database of Geographic Information System for Traditional Chinese Medicine. Soil samples from the sampling sites were collected. Effective boron and iron, available nitrogen and potassium, as well as other trace elements and soil nutrients, were determined by conventional soil physicochemical property assay methods. Analytical methods of biostatistics and numerical taxonomy were used to divide ecotypes of the three main Panax quinquefolium L. producing areas in China based on ginsenoside content, climate, soil and other ecological factors. To our knowledge, this is the first time that ecological division of P. quinquefolium L. producing areas in China has ever been conducted. The results show that there are two chemoecotypes of P. quinquefolium L. in China: ginsenoside Rb1-Re from outside Shanhaiguan, and ginsenoside Rg2-Rd from inside Shanhaiguan. Similarly, there are two types of climatic characteristics: inside Shanhaiguan (Beijing, Shandong) and outside Shanhaiguan (Northeast). This suggests that the formation and differentiation of chemoecotypes of P. quinquefolium L. is closely related to variability of the climatic and geographical environment. Additionally, ecological variation of the three main producing areas, characteristics of two climatic ecotypes, and soil characteristics are also discussed and summarized. These results provide experimental scientific evidence of the quality variation and ecological adaptation of P. quinquefolium L. from different producing areas. They also deepen our understanding of the biological nature of Daodi P. quinquefolium L. formation, and offer novel research models for other multi-origin, multi-Daodi Chinese herbal medicines ecotypes. In addition, the results demonstrate the critical need for improving quality, appropriate ecological regionalization and promoting industrialized development of P. quinquefolium L.

[Quantitative study on ecological suitability of Chinese herbal medicine based on GIS].

The quality of Chinese herbal medicine is closely related to its producing region. In order to apply mathematical models to do a quantitative study on the suitability of Chinese herbal medicine, it is necessary to study on the ecological factors and the interpolation of climatic data, which influence the Chinese herbal medicine growth. The paper firstly studied the judgment standard of ecological index from the points of ecology and statistics, and how to calculate the optimum range values and the weight of each ecological factor. Secondly, meteorological element data is essential data in analyzing the suitable region of Chinese herbal medicine, and the spatial distribution of meteorological elements is closely related to terrain environment, so, in order to make the results close to true value by the greatest degree. The paper adopted multiple linear regression interpolation method which based on DEM. The paper distinguished the factor system of suitable region and interpolation on the point of datumization, and made a study on it about some key issues.