Although microplastic pollution jeopardizes both terrestrial and aquatic ecosystems, the movement of plastic particles through terrestrial environments is still poorly understood. Agricultural soils exposed to different managements are important sites of storage and dispersal of microplastics. This study aimed to identify the abundance, distribution, and type of microplastics present in agricultural soils, water, airborne dust, and ditch sediments. Soil health was also assessed using soil macroinvertebrate abundance and diversity. Sixteen fields were evaluated, 6 of which had been exposed to more than 5 years of compost application, 5 were exposed to at least 5 years of plastic mulch use, and 5 were not exposed to any specific management (controls) within the last 5 years. We also evaluated the spread of microplastics from the farms into nearby water bodies and airborne dust. We found 11 types of microplastics in soil, among which Light Density Polyethylene (LDPE) and Light Density Polyethylene covered with pro-oxidant additives (PAC) were the most abundant. The highest concentrations of plastics were found in soils exposed to plastic mulch management (128.7 ± 320 MPs.g-1 soil and 224.84 ± 488 MPs.g-1 soil, respectively) and the particles measured from 50 to 150 μm. Nine types of microplastics were found in water, with the highest concentrations observed in systems exposed to compost. Farms applying compost had higher LDPE and PAC concentrations in ditch sediments as compared to control and mulch systems; a significant correlation between soil polypropylene (PP) microplastics with ditch sediment microplastics (r2 0.7 p 0.05) was found. LDPE, PAC, PE (Polyethylene), and PP were the most abundant microplastics in airborne dust. Soil invertebrates were scarce in the systems using plastic mulch. A cocktail of microplastics was found in all assessed matrices.

Research on the poverty risk caused by geological disasters in disaster-prone areas is a useful exploration to coordinate social economic development with disaster prevention and reduction, and is of great significance to the regional sustainable development. Based on statistical data and spatial data, this paper takes Sichuan Province as the typical research area. Remote sensing and geographic information technology are used to study the poverty risk caused by disasters based on the quantitative evaluation of geological disasters risk and regional development level. The spatial differentiation characteristics of poverty risk caused by disasters are explored on the 1 km × 1 km grid scale. The results indicate that (1) the overall risk of geological disasters in Sichuan Province is relatively high, with high and relatively high risk areas accounting for more than 40% and low and relatively low risk areas accounting for less than 30%. The risks in Mountain and Ravine Areas are significantly higher than other areas. (2) The regional development level in Sichuan Province is relatively high, but with significant spatial differences. The development level of high-altitude areas and remote mountainous areas is quite different from that of the Chengdu Plain in the middle Sichuan Province. The uneven development in the east, middle, and west is a prominent problem. (3) The poverty risk caused by disasters is high, and the spatial pattern presents a characteristic of “high in the west and low in the east” with high positive spatial correlation. High-High Cluster Areas are mainly distributed in western and southwestern Sichuan. Low-Low Outlier Areas are mainly distributed in Chengdu Plain and Hilly Areas of Sichuan Basin. High-Low Outlier and Low–High Outlier Areas occupy a relatively small percentage with scattered distribution. This paper provides some theoretical support for policy formulation and management of coordinated development of regional socioeconomic and ecological environment.

Blumea balsamifera is a famous Chinese Minority Medicine, which has a long history in Miao, Li, Zhuang, and other minority areas. In recent years, due to the influence of natural and human factors, the distribution area of B. balsamifera resources has a decreasing trend. Therefore, it is very important to analyze the suitability of B. balsamifera in China. Following three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) under 2050s and 2070s, geographic information technology (GIS) and maximum entropy model (MaxEnt) were used to simulate the ecological suitability of B. balsamifera. The contents of L-borneol and total flavonoids of B. balsamifera in different populations were determined by gas chromatography (GC) and ultraviolet spectrophotometry (UV). The results showed that the key environmental variables affecting the distribution of B. balsamifera were mean temperature of coldest quarter (6.18–26.57 ℃), precipitation of driest quarter (22.46–169.7 mm), annual precipitation (518.36–1845.29 mm), and temperature seasonality (291.31–878.87). Under current climate situation, the highly suitable habitat was mainly located western Guangxi, southern Yunnan, most of Hainan, southwestern Guizhou, southwestern Guangdong, southeastern Fujian, and western Taiwan, with a total area of 24.1 × 10⁴ km². The areas of the moderately and poorly suitable habitats were 27.57 × 10⁴ km² and 42.43 × 10⁴ km², respectively. Under the future climate change scenarios, the areas of the highly, moderately, and poorly suitable habitats of B. balsamifera showed a significant increasing trend, the geometric center of the total suitable habitats of B. balsamifera would move to the northeast. In recent years, the planting area of B. balsamifera has been reduced on a large scale in Guizhou, and its ex situ protection is imperative. By comparison, the content of L-borneol, total flavonoids and fresh leaf yield had no significant difference between Guizhou and Hainan (P > 0.05), which indicated that Hainan is one of the best choice for ex situ protection of B. balsamifera.

To cope with climate change, it is of great importance to describe the temporal and spatial evolution of climate change vulnerability and its driving factors. Therefore, this paper establishes a comprehensive index of vulnerability to climate change based on the vulnerability scoring diagram (VSD) framework. Moran’s I index is used to study the spatial evolution characteristics of vulnerability, and spatial regression analysis is used to explore the factors influencing the spatial distribution of vulnerability. The results show that (1) the climate change vulnerability of China has decreased over time, and the sensitivity state is relatively stable; however, the annual change in exposure and adaptive capacity is significant. (2) The western region of China is more vulnerable than the eastern region, and the most vulnerable provinces are Guizhou and Gansu. (3) The regional vulnerability is generally in a significant spatial agglomeration state. (4) Finally, the driving factors of the spatial distribution of climate change vulnerability include forest coverage, the urban-rural income gap and information technology. These recommendations provide detailed discussions and scientific information for mitigating global warming and formulating long-term emission reduction targets, thereby optimizing resource allocation and providing spatial governance directions for the formulation of adaptation policies.

With the rapid development of logistics park, how to evaluate and optimize the ecological efficiency of logistics park to achieve its sustainable development has become a concern of academia. In order to achieve this goal, this paper puts forward a method based on emergy, which processes the data in a unified dimension. By constructing the ecological efficiency evaluation model of logistics park, it quantitatively evaluates the ecological efficiency of logistics park, and analyzes the correlation between various factors and ecological efficiency. The application results of H logistics park show that fuel oil, information technology, net profit, and waste gas are closely related to the ecological efficiency of logistics park, and the correlation coefficients are 0.8248, −0.6949, 0.8544, and 0.7661, respectively. On this basis, the paper puts forward some suggestions to improve the ecological efficiency of the logistics park. This paper provides theoretical and methodological support for the evaluation and optimization of the ecological efficiency of the logistics park.

Fritillariae Cirrhosae Bulbus (FCB) is a famous traditional Chinese medicine, mainly used for relieving cough and resolving phlegm. According to Chinese Pharmacopoeia (2020), the medicine comes from dried bulbs of five species and one variety in Fritillaria. Due to climate change and human disturbance, the wild resources have become critically endangered in recent years. Following three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) under 2050s and 2070s, geographic information technology (GIS) and maximum entropy model (MaxEnt) were used to simulate the ecological suitability of FCB, a third-grade rare and endangered medicinal plant species. The results showed that the key environmental variables affecting the distribution of FCB were altitude, human activity intensity, and mean temperature of coldest quarter. Under current climate situation, the highly suitable areas were mainly located in the east of Qinghai Tibet Plateau, including Western Sichuan, southeastern Tibet, southern Gansu, Northwestern Yunnan, and Eastern Qinghai, with a total area of 31.47×10⁴ km², the area within the nature reserve was 7.13×10⁴ km², indicating that there was a large protection gap. Under the future climate change scenarios, the areas of the highly and poorly suitable areas of FCB showed a decreasing trend, while the areas of the moderately and total suitable areas showed an increasing trend. The geometric center of the total suitable area of the medicine will move to the northwest. The results could provide a strategic guidance for protection,development, and utilization of FCB though its prediction of potential distribution based on the key variables of climate change.

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations.

There is an increasing interest in product recovery, closed-loop supply chains, and reverse logistics (RL) for mitigating environmental impairment. Although RL is becoming a mandatory policy in developed countries, it is still in an embryonic stage in some industrial sectors of emerging economies. The purpose of this study is twofold: (1) identify the critical factors to the successful implementation of RL in the Brazilian pharmaceutical care process (PCP) and (2) determine the cause-and-effect relationships among them. We use snowball sampling to select the relevant RL studies and deductive reasoning and classification to identify the critical factors and a grey decision-making trial and evaluation laboratory (DEMATEL) to evaluate the cause-and-effect relationships among them. The study revealed management, collaboration, information technology, infrastructure, policy, financial and economic, end-of-life management practices, and logistic performance factors as the most relevant factors to the successful implementation of RL in the Brazilian PCP. The end-of-life management practices were identified as the most critical factor, and information technology was identified as the least critical factor. We further determined the end-of-life management practices and policy have the strongest casual relationship. The municipal PCP coordinators can use the findings of this study to formulate mitigating strategies to identify and eliminate barriers to the successful implementation of RL in the Brazilian PCP.

As one of the important problems in global change, elevated ultraviolet-B (UV-B) radiation induced by the depletion of stratospheric ozone layer has received more and more attentions around the world. Field experiment with barley was conducted to investigate the effects of elevated UV-B radiation on microbial biomass carbon and nitrogen in rhizosphere and nonrhizosphere soil. The experiment was designed with two UV-B radiation levels, i.e., elevated (E, simulating 25% stratospheric ozone depletion) and ambient (A, control), and performed at the Station of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing, China. Compared with the control, elevated UV-B radiation significantly depressed shoot biomass by 13.2–42.6% and root biomass by approximately 50% from jointing to ripening stage. Elevated UV-B radiation significantly increased microbial biomass C and N in nonrhizosphere soil in most cases, but significantly decreased microbial biomass C and N in rhizosphere soil. Further researches are needed to elucidate whether the above findings are connected with the changes in composition and amount of root exudates induced by elevated UV-B radiation, which can mainly affect the dynamics of soil microbial biomass.

The collaborative agglomeration of manufacturing and producer services is an essential tool for the green transformation of China’s economic model. This paper explores the impact of industrial collaborative agglomeration on carbon intensity, using the spatial Durbin model (SDM) based on China’s provincial panel data from 2012 to 2019. The empirical results indicate that there is an inverted N-shaped relationship between industrial collaborative agglomeration and carbon intensity, with the turning points of 2.5255 and 2.8575. Regional industrial collaborative agglomeration tends to initially reduce carbon intensity, then aggravates to carbon emission, then finally inhibits carbon intensity. There is an obvious heterogeneity in the impact of producer-service subsectors and manufacturing collaborative agglomeration on carbon intensity. When the industrial collaborative agglomeration level exceeds a certain threshold, the clustering of information transmission, software and information technology service, and financial intermediation service have the greatest emission reduction potential. Industrial collaborative agglomeration has obvious spatial spillover effect, and carbon intensity has obvious spatial convergence effect. This paper provides some novelties for research perspectives on carbon intensity reduction and theoretical references for the development and implementation of differentiated industrial collaborative agglomeration policies.