碳汇造林项目促进了当地经济发展吗?--基于四川县域面板数据的PSM-DID实证研究

林业是重要的碳汇资源,在减缓全球气候变化、改善自然生态环境、促进经济可持续发展等方面有着至关重要的作用。作为林业碳汇的重要实现形式,碳汇造林项目兼具生态保护、促进经济发展与贫困减缓等重要功能,其实施成效究竟如何需要进一步验证。为此,本文从理论上分析了碳汇造林项目对县域经济发展的影响机理,利用2000—2016年四川47个县域的面板数据,采用PSM-DID模型估计了碳汇造林项目对县域经济发展的平均效应和动态效应,并对其影响机理进行了验证。结果显示:①碳汇造林项目的实施显著地促进了地区实际GDP和人均实际GDP的增长,这一结论在进行稳健性检验后依然成立;②囿于项目周期较长,此促进作用在短期内尚不能立竿见影,具有明显的滞后效应,且实施的时间越长,对当地经济发展的促进作用越大;③碳汇造林项目主要通过优化当地产业结构、提高居民储蓄率、提升地区政府财政收支水平等途径促进当地经济发展。因此,为更好地发挥碳汇造林项目对县域经济发展的促进作用,应继续拓展碳汇造林项目的覆盖区域,加大专项投资力度,引导碳汇造林项目向生态脆弱的深度贫困地区倾斜;在更加注重碳汇造林项目的长期效应的同时,应建立完善项目运行的长效稳定机制,防范潜在的自然与市场风险,保障项目对地区经济发展的长期驱动力;加快改善地区的融资环境,鼓励居民和企业将储蓄和融资能力有效转化为投资能力,充分依托碳汇造林项目促进当地经济可持续发展。     

以Hartwick准则破解“资源的诅咒”

一些资源禀赋较高的国家或地区,一直以来经济社会发展未充分享受自然资源带来的红利,甚至陷入贫困和动荡,这一现象被称作"资源的诅咒";在我国,也有不少资源型城市在发展过程中由于资源的耗竭而陷入困境。经济学家Hartwick对资源枯竭区域发展进行了深入研究,并提出"Hartwick准则"对这一类区域的发展进行了理论指导。本文对Hartwick准则进行简要介绍,以这一准则在非洲国家博茨瓦纳的钻石开发中的应用进行分析,并依据理论和经验,对我国一些资源型区域的发展提出建议。     

农村变电站生活污水处理现状与探讨

我国大部分变电站位于农村地区,因无接入城市污水管网条件,农村变电站生活污水需就地处理后达标排放。变电站生活污水存在水量少、时变化系数大等特点,现有处理工艺不能正常运行或无法达标排放。本文借鉴农村生活污水处理技术,提出了生物组合法处理对策,可为变电站生活污水处理提供参考。     

大气环境监测全过程质量控制研究

我国经济飞快的发展速度,不但丰富了人们的生活内容、方便了人们的生活,而且还在人们生活中产生了一些负面影响,大气污染问题已经引起了国家政府以及我国民众的一致关注,国家还为此制定并颁布了相关的整顿治理措施,在大气环境治理方面,大气监测是重要手段,本文对大气环境监测全过程质量控制问题展开分析研究。     

Study on the measurement and the changing trend of the energy use of China’s economic sectors: based on cross-region input-output model

Environmental Science and Pollution Research - The consumption of fossil energy is the major cause of environmental pollution. Effectively reducing the fossil energy use has important significance...     

Study on the relationship between the incidence of influenza and climate indicators and the prediction of influenza incidence

In recent 2 years, the incidence of influenza showed a slight upward trend in Guangxi; therefore, some joint actions should be done to help preventing and controlling this disease. The factors analysis of affecting influenza and early prediction of influenza incidence may help policy-making so as to take effective measures to prevent and control influenza. In this study, we used the cross correlation function (CCF) to analyze the effect of climate indicators on influenza incidence, ARIMA and ARIMAX (autoregressive integrated moving average model with exogenous input variables) model methods to do predictive analysis of influenza incidence. The results of CCF analysis showed that climate indicators (PM2.5, PM10, SO₂, CO, NO2, O₃, average temperature, maximum temperature, minimum temperature, average relative humidity, and sunshine duration) had significant effects on the incidence of influenza. People need to take good precautions in the days of severe air pollution and keep warm in cold weather to prevent influenza. We found that the ARIMAX (1,0,1)(0,0,1)₁₂ with NO₂ model has good predictive performance, which can be used to predict the influenza incidence in Guangxi, and the predicted incidence may be useful in developing early warning systems and providing important evidence for influenza control policy-making and public health intervention.

     

Emission characteristics of PM,heavy metals,and dioxins in flue gases from sintering machines with wet and semi-dry flue gas desulfurization systems

Environmental Science and Pollution Research - In iron and steel industry, sintering process releases large amount and different kinds of pollutants. Most sintering plants had applied the dust...     

Boosting freshwater fish conservation with high-resolution distribution mapping across a large territory

The lack of high-resolution distribution maps for freshwater species across large extents fundamentally challenges biodiversity conservation worldwide. We devised a simple framework to delineate the distributions of freshwater fishes in a high-resolution drainage map based on stacked species distribution models and expert information. We applied this framework to the entire Chinese freshwater fish fauna (>1600 species) to examine high-resolution biodiversity patterns and reveal potential conflicts between freshwater biodiversity and anthropogenic disturbances. The correlations between spatial patterns of biodiversity facets (species richness, endemicity, and phylogenetic diversity) were all significant (r = 0.43–0.98, p < 0.001). Areas with high values of different biodiversity facets overlapped with anthropogenic disturbances. Existing protected areas (PAs), covering 22% of China's territory, protected 25–29% of fish habitats, 16–23% of species, and 30–31% of priority conservation areas. Moreover, 6–21% of the species were completely unprotected. These results suggest the need for extending the network of PAs to ensure the conservation of China's freshwater fishes and the goods and services they provide. Specifically, middle to low reaches of large rivers and their associated lakes from northeast to southwest China hosted the most diverse species assemblages and thus should be the target of future expansions of the network of PAs. More generally, our framework, which can be used to draw high-resolution freshwater biodiversity maps combining species occurrence data and expert knowledge on species distribution, provides an efficient way to design PAs regardless of the ecosystem, taxonomic group, or region considered.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

Improved product selectivity of electrochemical reduction of carbon dioxide by tuning local carbon dioxide concentration with multiphysics models

Environmental Chemistry Letters - Electrochemical reduction of carbon dioxide (CO2) is promising to alleviate carbon emissions and produce fuels and materials in a circular way, yet effective...