旅游业发展对中国碳排放的影响——基于中国东、中、西部的比较分析

在“双碳”战略目标下,深入研究中国旅游业对碳排放的影响,对科学制定减排政策,发展低碳旅游,以及应对气候变化有着重要的理论和现实意义。使用2003-2019年除港澳台和西藏之外的30个省市面板数据,从国内旅游和入境旅游的视角,结合面板单位根、协整、格兰杰因果检验,利用固定效应模型和随机效应模型探究东、中、西部旅游业发展与碳排放的关系。研究结果表明:(1)中国旅游业发展与碳排放之间均存在长期均衡关系。(2)入境旅游对碳排放不存在显著影响,国内旅游对碳排放存在显著正向影响。(3)东、中、西部地区的旅游业和碳排放关系存在差异,其中东部和中部地区国内旅游收入每提高1%将导致其碳排放总量分别增加2.313%和7.531%,而西部地区国内旅游收入提高1%将导致其碳排放总量减少1.306%。     

呼包鄂榆城市群耦合空间碳排放生态网络构建

构建生态网络是维持景观连通性、提升包括固碳在内的生态系统服务功能的重要手段。为了更好地响应固碳增汇目标及其政策要求,有必要将空间碳排放因素纳入区域生态网络分析框架。选择高能耗、高碳排且生态脆弱的呼包鄂榆城市群作为研究区,采用生态系统服务和连通性分析识别生态源地,并结合电路理论和重力模型提取生态廊道,得到区域景观生态格局;通过获取夜间灯光数据模拟得到城市群栅格尺度碳排放空间格局,并与景观生态格局进行空间叠加,以此补充“生态-碳排”耦合节点和规划廊道,进而构建考虑区域碳排放空间格局的城市群生态网络。结果表明：1)仅考虑生态因素构建的区域生态网络东西两侧生态源地连通性不足,网络呈“中部阻断型”分布;2)区域碳排放存在明显空间特征,高值区出现在人为生态扰动显著的中部矿产资源开发区和主要城镇地区;3)通过耦合区域碳排放格局,补充了23个“生态-碳排”耦合节点和67条规划廊道,生态网络结构由树状转变为蜂巢状,网络闭合度、线点率和连接度分别提升了92%、30.48%和27.45%。因此,通过耦合空间碳排放因素改进的生态网络构建方法,对于提高生态网络的多功能性和稳定性,以及促进以增加碳汇能力为目标的生...     

中国农村居民生活氮素流动特征

人类生活消费是陆地生态系统氮素流动的主要驱动力。定量核算和评估农村居民生活消费氮产生(N_RUR)及其活性氮(Nr)排放特征,对农村氮的可持续管理和生态环境改善具有重要的指导意义。以中国为例(2000—2020年),建立了N_RUR的产生及其活性氮排放核算框架。结果表明：20年来N_RUR上升了36.7%,年均5.62 Tg/a,食物消费氮是最大的贡献源(43.2%),工业日用品和家庭生活燃料消费氮分别占31.5%和25.3%;Nr排放量占N_RUR的25.4%(年均1.43 Tg/a),其以年均1.3%速率下降;NH₃挥发是最大的Nr排放源(50.1%),其次为排入地表水的Nr(31.0%)、NO_x(15.8%)和N₂O(2.0%),排入地下水的Nr仅占1.1%。加大人类粪尿排泄物的处置能力,减少秸秆燃料的使用比例、优化农村居民生活能源消费结构对农村居民生活消费Nr减排至关重要。     

Effect of condensed tannins in rations of lactating dairy cows on production variables and nitrogen use efficiency

The objective of this study was to evaluate the effect of supplemented condensed tannins (CT) from the bark of the Black Wattle tree (Acacia mearnsii) on production variables and N use efficiency in high yielding dairy cows. A feeding trial with 96 lactating German Holstein cows was conducted for a total of 169 days, divided into four periods. The animals were allotted to two groups (control (CON) and experimental (EXP) group) according to milk yield in previous lactation, days in milk (98), number of lactations and BW. The trial started and finished with a period (period 1 and 4) where both groups received the same ration (total-mixed ration based on grass and maize silage, ensiled sugar beet pulp, lucerne hay, mineral premix and concentrate, calculated for 37 kg energy-corrected milk). In between, the ration of EXP cows was supplemented with 1% (CT1, period 2) and 3% of dry matter (DM) (CT3, period 3) of a commercial A. mearnsii extract (containing 0.203 g CT/g DM) which was mixed into the concentrate. In period 3, samples of urine and faeces were collected from 10 cows of each group and analyzed to estimate N excretion. Except for a tendency for a reduced milk urea concentration with CT1, there was no difference between groups in period 2 (CON v. CT1; P>0.05). The CT3 significantly reduced (P<0.05) milk protein yield, the apparent N efficiency (kg milk N/k feed N) and milk urea concentration; but total milk yield and energy-corrected milk yield were not affected by treatment. Furthermore, as estimated from 10 cows per group and using urinary K as a marker to estimate the daily amount of urine voided, CT3 caused a minor shift of N compounds from urine to faeces, as urea-N in urine was reduced, whereas the N concentration in faeces increased. As an improvement in productivity was not achieved and N use efficiency was decreased by adding the CT product it can be concluded that under current circumstances the use in high yielding dairy cows is not advantageous.     

Life cycle of CO2-emissions from electric vehicles and gasoline vehicles utilizing a process-relational model

This article aims at estimating life cycle CO₂ emissions from electric vehicles (EV) and gasoline vehicles (GV), although the estimation in this study is not an LCA according to ISO14040s. For this purpose, a mathematical tool called the Process-relational model was developed. The Process-relational model is used for establishing life cycle inventories. The model has a structure which improved the principle of input-output analysis in econometrics that only one product is generated by one process. This model enabled us to overcome difficulties of LCA in retracing complicated repercussions among production systems. Then, life cycle CO₂, emissions from electric vehicles (EV) and gasoline vehicles (GV) were estimated with this model. Estimated results indicated that the manufacture and driving of EV resulted in less CO₂ emissions than chose of GV. However, the difference between EV and GV dramatically changed depending on traffic situations. Namely, the difference became larger as the average velocity of the vehicles became lower. We also compared CO₂, emission from manufacturing EV with that from driving EV. The share of manufacture was shown to increase in total CO₂, emissions as the average velocity of the EV became higher. In conclusion, we clarified the direction of research and development of EV and GV for reducing the life cycle CO₂.     

Client-side energy and GHGs assessment of advertising and tracking in the news websites

Electronic devices consume energy both in the production and the use phase. Furthermore, the “hidden” impacts linked to their use are not frequently assessed and they depend on the behavior of the users, besides the servers and complex web networks. It must be underlined that many websites employ ads and trackers as part of their monetization strategy and, in order for online ads and trackers to work, they add an additional code to be executed on the users’ machines, which in turn requires more processing power. Considering that the Internet had an estimated 4.9 billion users in 2021, the global energy and carbon impacts of online ads and trackers might be significant. To investigate this phenomenon, we designed a novel automated framework for bottom-up estimation of greenhouse gas (GHG) emissions attributable to software using exclusively free and open source software. Our process involved the building of a random sample of global news websites which we visited with and without an ad-blocker, each time collecting power usage in identical conditions. The gathered data were put into an ordinary least squares (OLS)-based linear regression model, which showed that ads and trackers on news websites require on average an additional 6.13 W of power on personal computers. This result was then tuned to global environmental and technological parameters to estimate that in 2019, on the client side, ads and trackers on the news websites consumed 0.61 TWh of electrical energy, emitted 0.29 MtCO₂eq of GHG, and cost all Internet users approximately 140 million USD (purchasing power parity) of electrical energy. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges .      

Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers

Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year⁻¹ in 2014, including 5.9 Tg N year⁻¹ (1.04, 95% confidence interval [95% CI]: 0.09–1.99 kg N ha⁻¹ year⁻¹) emitted from forest, 1.7 Tg N year⁻¹ (0.68, 95% CI: 0.10–1.26 kg N ha⁻¹ year⁻¹) from grassland, and 1.8 Tg N year⁻¹ (0.98, 95% CI: 0.42–1.53 kg N ha⁻¹ year⁻¹) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.     

Comparing global warming potential,energy use and land use of organic,conventional and integrated winter wheat production

To ensure a sustainable food supply for the growing population, the challenge is to find agricultural systems that can meet production requirements within environmental constraints and demands. This study compares the impacts of winter wheat production on energy use, land use and 100 years Global Warming Potential (GWP₁₀₀) under different arable farming systems and farming practices. Life cycle assessment was used to simulate the impacts of organic, conventional and integrated farming (IF) systems along the production chain from input production up to the farm gate. The IF system models were designed to combine the best practices from organic and conventional systems to reduce negative environmental impacts without significant yield reductions. An integrated system that used food waste digestate as a fertiliser, and utilised pesticides and no‐tillage had the lowest energy use and GWP per functional unit of 1000 kg wheat output. When the impacts of some specific practices for reducing energy use and GWP were compared, the highest energy use reductions were achieved by replacing synthetic nitrogen fertilisers with anaerobically treated food waste or nitrogen fixing crops, increasing yields through crop breeding and using no‐tillage instead of ploughing. The highest GWP reductions were achieved by using nitrification inhibitors, replacing synthetic nitrogen fertilisers and increasing yields. The major contributors to the uncertainty range of energy use were associated with machinery fuel use and the assumed crop yields. For GWP results, the main source of uncertainty related to the N₂O emissions. In conclusion, farming systems that combine the best practices from organic and conventional systems have potential to reduce negative environmental impacts while maintaining yield levels.     

The good,the bad,and the future: Systematic review identifies best use of biomass to meet air quality and climate policies in California

California has large and diverse biomass resources and provides a pertinent example of how biomass use is changing and needs to change, in the face of climate mitigation policies. As in other areas of the world, California needs to optimize its use of biomass and waste to meet environmental and socioeconomic objectives. We used a systematic review to assess biomass use pathways in California and the associated impacts on climate and air quality. Biomass uses included the production of renewable fuels, electricity, biochar, compost, and other marketable products. For those biomass use pathways recently developed, information is available on the effects—usually beneficial—on greenhouse gas (GHG) emissions, and there is some, but less, published information on the effects on criteria pollutants. Our review identifies 34 biomass use pathways with beneficial impacts on either GHG or pollutant emissions, or both—the “good.” These included combustion of forest biomass for power and conversion of livestock-associated biomass to biogas by anaerobic digestion. The review identified 13 biomass use pathways with adverse impacts on GHG emissions, criteria pollutant emissions, or both—the “bad.” Wildfires are an example of one out of eight pathways which were found to be bad for both climate and air quality, while only two biomass use pathways reduced GHG emissions relative to an identified counterfactual but had adverse air quality impacts. Issues of high interest for the “future” included land management to reduce fire risk, future policies for the dairy industries, and full life-cycle analysis of biomass production and use.     

Environmental footprinting of hospitals: Organizational life cycle assessment of a Canadian hospital

Healthcare is a critical and complex service sector with direct and indirect greenhouse gas (GHG) emissions amounting to 5%–10% of the national total in developed economies like Canada and the United States. Along with a growing, albeit sporadic, set of life cycle assessment (LCA) (and “carbon footprinting”) studies of specific medical products and procedures, there is growing interest in “environmental footprinting” of hospitals. In this article, we advance this rapidly evolving area through a comprehensive organizational LCA of a 40-bed hospital in British Columbia, Canada, in its 2019 fiscal year. Our results indicate that the total environmental footprint of the hospital includes, among other things, global warming potential of 3500–5000 t CO₂ eq. (with 95% confidence). “Hotspots” in this footprint are attributable to energy and water use (and wastewater released), releases of anesthetic gases (which are potent GHGs), and the upstream production of the thousands of materials, chemicals, pharmaceuticals, and other products used in the hospital. The generalizability and comparability of these results are limited by inconsistencies across the few environmental footprinting studies of hospitals conducted to date. Nonetheless, our novel methodological approach, in which we compiled new LCA data for 200 goods and services used in healthcare—strategically selected to statistically represent the 2927 unique products in the hospital's “supply-chains”—has broad applicability in healthcare and beyond.