Sample preparation for fatty acid analysis in biological samples with mass spectrometry-based strategies.

Fatty acids (FAs) have attracted many interests for their pivotal roles in many biological processes. Imbalance of FAs is related to a variety of diseases, which makes the measurement of them important in biological samples. Over the past two decades, mass spectrometry (MS) has become an indispensable technique for the analysis of FAs owing to its high sensitivity and precision. Due to complex matrix effect of biological samples and inherent poor ionization efficiency of FAs in MS, sample preparation including extraction and chemical derivatization prior to analysis are often employed. Here, we describe an updated overview of FA extraction techniques, as well as representative derivatization methods utilized in different MS platforms including gas chromatography-MS, liquid chromatography-MS, and mass spectrometry imaging based on different chain lengths of FAs. Derivatization strategies for the identification of double bond location in unsaturated FAs are also summarized and highlighted. The advantages, disadvantages, and prospects of these methods are compared and discussed. This review provides the development and valuable information for sample pretreatment approaches and qualitative and quantitative analysis of interested FAs using different MS-based platforms in complex biological matrices. Finally, the challenges of FA analysis are summarized and the future perspectives are prospected.

The effect of economic growth pressure on green technology innovation: Do environmental regulation, government support, and financial development matter?

Green technology improvement is critical in promoting green development and mitigating negative externalities. Exploring the effect of economic growth pressure (EGP) on green technology innovation (GTI) is important for coordinated economic growth and green transformation. Using the data from 285 cities in China during 2006-2018, this study investigates the influence of EGP on GTI by taking the difference between economic growth target and previous year's actual growth rate to represent the EGP. The results indicate that EGP negatively affects GTI. When there is a 1% increase in EGP, green patent applications will fall by 3.2%. Furthermore, the heterogeneity analysis indicates that the negative effect of EGP is especially significant in western China compared with eastern and central regions. In addition, we find various nonlinear moderating effects between EGP and GTI by using panel threshold model. Specifically, EGP and GTI show an inverted U-shaped relationship with EGP increasing. Meanwhile, only when environmental regulation, government support, and financial development cross the thresholds will EGP have a significant role in promoting GTI. This study provides helpful implications for decision-makers to adopt a more reasonable combination of policy tools to achieve economic growth targets and low-carbon transformation.

What is the spatiotemporal relationship between urbanization and ecosystem services? A case from 110 cities in the Yangtze River Economic Belt, China.

Rapid urbanization has altered landscape patterns and ecological functions, causing a decline in ecosystem service and generating many ecological and environmental issues. Studying the spatiotemporal interaction between urbanization and ecosystem service (ES) can provide effective supports for regional sustainability and policy formulation. This research utilizes the Yangtze River Economic Belt (YREB) as a case to analyze the spatiotemporal interaction between multi-urbanization indicators and multi-ESs over a large-scale region. The results show that the urbanization process in the YREB evolves from a rapidly growing state to a steady state with a slower rise. The urbanization level of the Yangtze River Delta urban agglomeration is relatively higher than the other regions. The distribution pattern of urbanization shows an overall characteristic of lower urbanization in the west and higher in the east. From 2009 to 2016, ecosystem service value (ESV) in the YREB decreased first and then increased, ESV in 2016 showed a reduction of 12.768 billion yuan compared with the 2009 level. ESV increases gradually from highly urbanized areas to those with lower levels of urbanization. Areas with high ESV levels are distributed at the middle reaches of YREB. There is a U-shaped curve relationship between urbanization and ESV, the ESV sharply increased when the urbanization index exceeded 0.6 in 2012. Land urbanization has the greatest impact on ESV among the four subtypes of urbanization indicators. Urbanization and ESV show the synergy relationship mostly in the eastern region, accounting for 18.18% of the total 110 cities. By contrast, they present the trade-off relationship in northern, southern and central regions, occupying 47.27% of the total observations. This study is helpful to provide scientific suggestions regarding the development of new urbanization, the protection of ESV, and the issue of how to achieve synergistic and sustainable development between them.

Spatial differences of ecosystem services and their driving factors: A comparation analysis among three urban agglomerations in China's Yangtze River Economic Belt.

Understanding the spatial distribution characteristics of ecosystem service value (ESV) and their underlying driving factors is critical for ecosystem service management. Using three national-level urban agglomerations in the Yangtze River Economic Belt, Cheng-Yu (CY), Middle-Reach Yangtze River (MRYR), and Yangtze River Delta (YRD), as a case study, this paper quantifies the ESVs and the spatial distribution characteristics, analyzes the driving factors of ESVs using the stochastic impacts by regression on population, affluence, and technology model (STIRPAT). The results specify that: (1) Over the study period 2009-2016, the total ESV of the three urban agglomerations decreases by 5498.70 million USD. The regulating, supporting, and cultural service decrease by 4607.60, 2648.01, and 1182.25 million USD, respectively, while the provisioning service increases by 2795.15 million USD. (2) ESV in MRYR undergoes the largest reduction of 4269.70 million USD, followed by CY and YRD with 1015.66 and 213.35 million USD from 2009 to 2016. (3) In 2016, among the 70 cities at the prefecture level or above, the cities with high total ESV, per unit area ESV, and per capita EVS are mainly distributed to the areas of the south Yangtze River of MRYR and YRD, MRYR, and MRYR and YRD, respectively. (4) In general, land use and cover, population are the main factors affecting ESVs, followed by economic, social and political factors. Among the three urban agglomerations, population, land use and cover basically have the equally important impacts on ESV in CY; land use and cover, especially the proportion of urban construction land has the greatest impact on ESV in MRYR; population, especially the urbanization rate has the greatest impact in YRD. The comparative analysis of the driving factors of ESVs in different regions is helpful to propose differentiated ecological protection policies and promote the increase of ESV accordingly.

What contributes to the regional inequality of haze pollution in China? Evidence from quantile regression and Shapley value decomposition.

Against the increasingly serious haze pollution in China, this paper is to compare the impacts of different factors on haze pollution in different regions, and understand the causes of regional inequality of haze pollution. In doing so, quantile regression and regression-based Shapley value decomposition are employed in this paper. The main results are as follows. (1) Population density and industrialization level have positive impacts on haze pollution, while economic development negatively influences haze pollution, however, the impact of environmental regulation on haze pollution is ineffective. (2) With quantile increasing, the effect of foreign direct investment on haze pollution changes from positive to negative, and the influence of energy intensity on haze pollution changes from negative to positive. (3) The decomposition results specify that the regional inequality in population density is the main cause of the regional disparities of haze pollution. The inequalities in industrialization level and regional factors are also important reasons, and the contribution of energy intensity cannot be ignored either. The regional gap of economic development is conducive to reducing the regional disparities of haze pollution.

A Comparative Analysis of Residential Energy Consumption in Urban and Rural China: Determinants and Regional Disparities.

Residential energy consumption (REC) has become increasingly important in constructing an energy-saving and environment-friendly society in China. The main purpose of this study is to provide a more in-depth analysis of the determinants of REC from an urban-rural segregation perspective, and quantify the contributions of individual determinants to the regional disparities of REC. Based on the extended STIRPAT (the stochastic impacts by regression on population, affluence, and technology) model, seemingly unrelated regression (SUR) estimation is employed to examine the impacts of various determinants of urban REC per capita (URECP) and rural REC per capita (RRECP) in a sample of China's 30 provinces over the period 2007⁻2016. Then, following the results of SUR, this paper tries to explore the reasons for interprovincial disparities of URECP and RRECP by using the Shapley value decomposition. The empirical results show that income level and heating lead to an increase in URECP, while other factors, including the share of natural gas, average temperature, child dependency ratio and gross dependency ratio, significantly decrease URECP. In terms of RRECP, it is shown that old-age dependency ratio, income level and the share of coal consumption positively influence RRECP, while average temperature has a negative effect on RRECP. Specially, the effect of gross dependency ratio on RRECP is positive, indicating the non-working-age population causes more energy use than the working-age population in rural areas. According to the Shapley decomposition, rather than social-economic variables, climate and heating factors contribute the most to the interprovincial differences in URECP. Furthermore, it is found that income level is the most important factor accounting for inter-provincial differences in RRECP. The findings of this research are of great interest, not only to scholars in REC-related fields, but also to decision makers.