[Impacts of Human Activities on the Net Primary Productivity of Vegetation in Chengde's Transitional Region from Plateau to Plain in the Context of Climate Change].

Chengde's transitional region from plateau to plain is located in the transition zone of agriculture and livestock and is extremely sensitive to climate change and human activities. This study used the net primary productivity(NPP) of vegetation as an evaluation index to quantify the degree impacts of climate change and human activities on vegetation change in the region. The Thornthwaite Memorial model was used to calculate the potential NPP, and the actual NPP was obtained based on MODIS NPP remote sensing images, using the difference between the actual and potential NPPs to express the amount of change in NPP owing to human activities. We used the slope trend and coefficient of variation method to analyze the trend and stability distribution of the actual NPP, potential NPP, and NPP influenced by human activities, and the correlation between actual NPP and annual precipitation and annual average temperature was analyzed using the correlation coefficient method. Finally, we quantified the impact of climate change and human activities on vegetation change in the region. The results showed that 99.87% of the vegetation in the region was improved and changed steadily, and the proportions of the areas showing positive correlation between actual NPP and annual precipitation and annual average temperature were 99.87% and 91.66%, respectively. The potential NPP showed an increasing trend from northwest to southeast, whereas the trend and stability of the potential NPP both showed an increasing trend from west to east. The area where climate change and human activities played a role in vegetation improvement accounted for 99.71%, and that affected by climate change accounted for 0.14%, with the proportion of human activities leading to vegetation degradation being 0.15%.

Geochemical characteristics and growth suitability assessment of Scutellaria baicalensis Georgi in the Earth's critical zone of North China.

Geochemical differentiation of soils has a series of consequences on plant and places pressure on the ecological environment. The quantitative evaluation of element migration in the Earth's critical zone is a challenging task. In this study, two demonstration study areas of Scutellaria baicalensis Georgi were selected, and multiple chemical weathering indexes, chemical loss fraction, mass migration coefficients and biological enrichment coefficient method were used to assess the ecological and geochemical suitability. The results show that for the element of Fe, Zn, Se, Cu, Co, Ni, Mo and Ge, the degree of weathering and soil maturation, were greater in the rhyolitic tuff area than in the Plagioclase gneiss area. In both research sites, the heavy metal level of samples in Scutellaria baicalensis Georgi did not exceed the standard limits. The plagioclase gneiss region's surface soil environment was more alkaline, and the content of soil organic matter was lower, resulting in a higher bioenrichment intensity of Ge, Co, Cu, and Se elements in Scutellaria baicalensis Georgi than in the rhyolite-tuff area. The elements of Cd, Nb, Mo, Pb and As are considerably enriched in the soil of the plagioclase gneiss area but lost by leaching in the soil of the rhyolite tuff area, which is connected to the interplay of elemental abundance and human impact in the parent materials. This study provides a good example of how to assess growth suitability of Chinese medicinal materials in the Earth's critical zone.

[Bioaccumulation and Translocation Characteristics of Heavy Metals in a Soil-Maize System in Reclaimed Land and Surrounding Areas of Typical Vanadium-Titanium Magnetite Tailings].

A total of 86 soil samples, 86 corn kernel samples, 50 tailings samples, and 33 ore rock samples were collected in reclaimed land and surrounding areas of typical vanadium-titanium magnetite tailings located in the Chengde Central Region and analyzed for 14 elements (P, Fe, Cu, Ni, Cd, Cr, Pb, Zn, Hg, Ti, Mn, and Mo) and speciation of heavy metals. This study investigated the bioaccumulation and translocation characteristics of heavy metals in a soil-maize system based on a descriptive statistical analysis, a geological accumulative index, bioconcentration factors, and a redundancy analysis. The results showed that the average accumulation index of surface soil followed an order of P > Cu > Fe2O3 > Cr > Ti > V > Ni > Mn > Cd > Zn > Mo > As > Pb > Hg, while the accumulation level of heavy metals was generally categorized as either no accumulation or moderate accumulation. Compared to China's soil environmental quality standard risk screening values (GB15618-2018), the over-standard rates of Cr and Cu were 2.32% and 1.16%, respectively. The content of Fe, Ti, As, Pb, and Mn in the corn kernels of the tailings and surrounding areas was relatively high, and the content of Mo, Ni, Cu, Zn, Cd, and Cr in the control area was relatively high. The over-standard rates of Ni, Zn, and Cu in the corn kernels were 13.61%, 13.23%, and 5.17% respectively, according to China's national food safety standard limits for contaminants in food (GB 2762-2017). The bioconcentration factors of Fe, Ti, As, Pb, and Mn in the corn kernels of the tailings and the surrounding areas were relatively higher, while the bioconcentration factors of Mo, Ni, Cu, Zn, Cd, and Cr were lower than in control area. The bioactive components of Cd accounted for 50.17%, which was the highest, followed by Ni, Zn, and Cu with average ratios of 13.61%, 13.23%, and 5.17%, respectively. Compared to the control area, the Pb, As and Hg elements in the soil samples of the reclaimed land showed a lower total amount but a higher bioavailability content and soil pH value, while the Cu and Hg elements showed a higher total amount but lower bioavailability content and soil pH value. These differences in total heavy metal concentrations, bioavailability amounts, and soil pH values made the bioconcentration intensity of As and Pb in the tailings reservoir and surrounding area relatively higher. When studying the ecological risk of heavy metal pollution or determining the remediation target value of reclaimed land in a mine tailings reservoir and the soil around the mine area, the bioavailable state limit of heavy metals should be should be taken into account as the evaluation standard.

[Seasonal Variation and Source Apportionment of Carbonaceous Species in PM2.5 in Chengde].

In order to study the seasonal variations and pollution sources of carbonaceous species in PM2.5 in Chengde, the concentration of these components was determined in atmospheric PM2.5 samples collected in January, April, July, and October 2019. The change in carbonaceous species were analyzed based on the estimation of the ratio of organic carbon(OC) to elemental carbon(EC), total carbonaceous aerosol(TCA), and secondary organic carbon(SOC). The source of these pollutants was determined by means of the backward trajectory and principal component analysis(PCA). The results showed that the mean mass concentrations of PM2.5, OC, and EC during the sampling period were(31.26±21.39) µg·m-3,(13.27±8.68) µg·m-3, and(2.80±1.95) µg·m-3, respectively. The seasonal variations of PM2.5 were:winter[(47.68±30.37) µg·m-3]>autumn[(28.72±17.12) µg·m-3]>spring[(26.59±15.32) µg·m-3]>summer[(23.17±8.38) µg·m-3], consistent with the trend of total carbon(TC), OC, and EC. The source of OC and EC during winter(R2=0.85) was similar. Based on the ratio of OC/EC, all four seasons were affected by traffic and coal-burning source emissions, and the most affected season by bituminous coal emissions was winter. The average concentration of TCA was(21.38±13.68) µg·m-3, which accounted for 68.39% of PM2.5. The order of secondary conversion rate(SOC/OC) was:spring(54.09%) >autumn(37.64%) >summer(32.91%) >winter(25.43%). The results of the backward trajectory simulation show that the pollutant concentrations carried by air masses are relatively low in spring and summer, and the transport channels of pollutants are southwest in autumn and northwest in winter. The results of the PCA showed that the key to reducing PM2.5 in Chengde is to control emissions from vehicle exhausts, and coal and biomass combustion sources.

[Determination of Heavy Metal Geochemical Baseline Values and Its Accumulation in Soils of the Luanhe River Basin, Chengde].

A total of 351 surface soil samples (0-20 cm) were collected from the Luanhe River Basin in Chengde City (a typical area of concentrated mineral resources) and analyzed for 12 heavy metals (Cu, Ni, Cd, Cr, Pb, Zn, Hg, V, Ti, Mn, As, and Co). The geochemical baseline values of the heavy metals were determined using the reference element method and the cumulative frequency curve method. Furthermore, the spatial structure and distribution characteristics of the heavy metals were assessed based on PCA and geostatistical analysis. The accumulation of heavy metal pollution in different types of soil and in association with different land use patterns was also evaluated using a geological accumulative index. The results showed that the geochemical baseline values of V, Ti, Cd, Pb, Mn, and Co in the surface soils of the Luanhe River Basin were higher than their background values for Hebei Province. In contrast, the geochemical baseline values of As, Zn, Cr, Cu, Ni, and Hg were lower than their background values. The average accumulation index of the surface soils followed the order of Cd > Pb > Cu > Ti > Mn > Zn > Cr > Ni > Co > V > Hg > As. More than 80% of the soil samples were categorized as having no accumulation or moderate accumulation of Pb, Ti, V, As, and Co, while over 70% of the soil samples were categorized as having no accumulation or moderate accumulation of Hg, Mn, Ni, Cu, As, Cd, and Cr. With respect to different soil types, the average accumulation index of heavy metals followed the order of fluvo-aquic soil>cinnamon soil>brown soil. With respect to land use types, the accumulation index of heavy metals followed the order of industrial and mining land > shrub forest land > agricultural land > woodland and grassland. The accumulation of Pb and Cd in the surface soils of agricultural land was relatively high in comparison to the other elements, with 27.69% and 25.38% of the samples being above the moderate accumulation level, respectively. The iron group elements Ti, V, Co, Ni, and Cr are likely to derive from naturally high geological background sources, while the spatial patterns of Cd, Pb, Zn, Mn, Cu, and As were associated with the combination of parent material and anthropogenic inputs. The accumulation of Hg was mainly influenced by human activities.

[Air Pollutant Emission Inventory and Impact of Typical Industries on PM2.5 in Chengde].

In this study, detailed activity level of typical sector in Chengde in 2013 was obtained through a full-coverage investigation. A comprehensive emission inventory with country-level resolution in 2013 was developed based on guide of atmospheric pollutant emission inventory and updated emission factors. Then, the emission inventory within 1 km×1 km grid was generated using source-based spastial surrogates including population, road network and landuse date. Furthemore, meteorology-air quality modeling system (WRF-CMAx) including Particulate Source Apportionment Technology (PSAT) module was established in order to evaluate the impact of topical sector (e. g., electric power, the production of construction materials, the metallurgical industry, etc.) on PM2.5 concentration in January, April, July and October which were considered as the representative months of winter, spring, summer and autumn. The results showed the total emission of SO2, NOx, TSP, PM10, PM2.5, CO, VOCs and NH3 in Chengde in 2013 was respectively 81134 t, 72556 t, 368750 t, 119974 t, 51152 t, 1281371 t, 170642 t and 81742 t. Industrial source was the main emission contributor of SO2, NOx, CO, VOCs, accounting for 89.5%, 51.9%, 82.5% and 45.6% of total emissions, respectively. The major emission source of NOx also included on-road and non-road mobile source, respectively accounting for 26.7% and 10.8%. The major emission source of TSP, PM10 and PM2.5 was fugitive dust, accounting for 76.7%, 65.6% and 46.54%, respectively. Ammonia emissions from animals and farm accounted for 67.1% and 15.8% of total emissions, respectively. The numerical simulation result showed that the fugitive dust, the others, the metallurgical industry and boilers industry had relatively higher contributions to PM2.5 concentration, accounting for 23.1%, 20.6%, 13.3% and 11.2%, respectively. These emission sources should be paid more attention during the decision-making with respect to control strategies.