Energy consumption and CO2 emissions in Tibet and its cities in 2014

Because of its low level of energy consumption and the small scale of its industrial development, the Tibet Autonomous Region has historically been excluded from China's reported energy statistics, including those regarding CO2 emissions. In this paper, we estimate Tibet's energy consumption using limited online documents, and we calculate the 2014 energy-related and process-related CO2 emissions of Tibet and its seven prefecture-level administrative divisions for the first time. Our results show that 5.52 million tons of CO2 were emitted in Tibet in 2014; 33% of these emissions are associated with cement production. Tibet's emissions per capita amounted to 1.74 tons in 2014, which is substantially lower than the national average, although Tibet's emission intensity is relatively high at 0.60 tons per thousand yuan in 2014. Among Tibet's seven prefecture-level administrative divisions, Lhasa City and Shannan Region are the two largest CO2 contributors and have the highest per capita emissions and emission intensities. The Nagqu and Nyingchi regions emit little CO2 due to their farming/pasturing-dominated economies. This quantitative measure of Tibet's regional CO2 emissions provides solid data support for Tibet's actions on climate change and emission reductions

Limited driving of elevated CO2 on vegetation greening over global drylands

Drylands are the world's largest biome and dominate the trends and interannual variability of global carbon sinks. Although a 'greening' trend of global drylands has been widely reported, large uncertainties remain in attributing its drivers. It is increasingly emphasized that elevated CO2 has greatly contributed to the vegetation greening over global drylands. Here we quantified the contributions of climate change, elevated CO2, and land use and land cover change (LULCC) on leaf area index (LAI) over drylands, using a process-based land surface model Noah-MP to investigate the drivers of vegetation change. The state-of-the-art model shows better performance in simulating the interannual variability of satellite-observed LAI over global drylands compared with that of the multi-model ensemble mean LAI from the TRENDY results. The area that LAI changes dominated by climate change (44.03%) is three times greater than that by CO2 (13.89%), and climate change also contributes most to the global drylands greening trend (55.07%). LULCC shows regional dominance over 13.35% of the global drylands, which is associated with afforestation, woody plant encroachment, and agricultural intensification. Our results imply that the vegetation greening area driven by elevated CO2 is much limited relative to the overwhelming climatic driving, which should be considered in predictions of trends and interannual variations of global carbon sinks

Sharing tableware reduces waste generation, emissions and water consumption in China’s takeaway packaging waste dilemma

China has a rapidly growing online food delivery and takeaway market, serving 406 million customers with 10.0 billion orders and generating 323kilotonnes of tableware and packaging waste in 2018. Here we use a top-down approach with city-level takeaway order data to explore the packaging waste and life-cycle environmental impacts of the takeaway industry in China. The ten most wasteful cities, with just 7% of the population, in terms of per capita waste generation, were responsible for 30% of the country's takeaway waste, 27-34% of the country's pollutant emissions and 30% of the country's water consumption. We defined one paper substitution and two sharing tableware scenarios to simulate the environmental mitigation potentials. The results of the scenario simulations show that sharing tableware could reduce waste generation by up to 92%, and environmental emissions and water consumption by more than two-thirds. Such a mechanism provides a potential solution to address the food packaging waste dilemma and a new strategy for promoting sustainable and zero-waste lifestyles. The online food delivery and takeaway market is growing in China, serving 406 million customers with 10.0 billion orders in 2018. Here, data from an online food delivery platform, life-cycle environmental impacts of packaging and tableware waste generated across 353 cities in China, and scenarios for paper alternatives and tableware sharing are presented

Detection of human influences on temperature seasonality from the 19th century

It has been widely reported that anthropogenic warming is detectable with high confidence after the 1950s. However, current palaeoclimate records suggest an earlier onset of industrial-era warming. Here, we combine observational data, multiproxy palaeo records and climate model simulations for a formal detection and attribution study. Instead of the traditional approach to the annual mean temperature change, we focus on changes in temperature seasonality (that is, the summer-minus-winter temperature difference) from the regional to whole Northern Hemisphere scales. We show that the detectable weakening of temperature seasonality, which started synchronously over the northern mid–high latitudes since the late nineteenth century, can be attributed to anthropogenic forcing. Increased greenhouse gas concentrations are the main contributors over northern high latitudes, while sulfate aerosols are the major contributors over northern mid-latitudes. A reduction in greenhouse gas emissions and air pollution is expected to mitigate the weakening of temperature seasonality and its potential ecological effects

Reconciling the Discrepancy of Post-Volcanic Cooling Estimated from Tree-Ring Reconstructions and Model Simulations over the Tibetan Plateau

Volcanic eruptions are a major factor influencing global climate variability, usually with a cooling effect. The magnitudes of post-volcanic cooling from historical eruptions estimated by tree-ring reconstructions differ considerably with the current climate model simulations. It remains controversial on what is behind such a discrepancy. This study investigates the role of internal climate variability (i.e., El Niño/Southern Oscillation (ENSO) warm phase) with a regional focus on the Tibetan Plateau (TP), using tree-ring density records and long historical climate simulations from the fifth Coupled Model Intercomparsion Project (CMIP5). We found that El Niño plays an important role behind the inconsistencies between model simulations and reconstructions. Without associated El Niño events, model simulations agree well with tree-ring records. Divergence appears when large tropical eruptions are followed by an El Niño event. Model simulations, on average, tend to overestimate post-volcanic cooling during those periods as the occurrence of El Niño is random as part of internal climate variability

Responses of terrestrial water cycle components to afforestation within and around the Yellow River basin

Reforestation has attracted worldwide attention because of its multiple environmental benefits, but its impact on water resources is complicated and still controversial. In this study, the authors conducted numerical experiments within and around the Yellow River basin under the Grain-for-Green project using the Weather Research and Forecasting model. The results showed that the terrestrial water cycle process was sensitive to land use/cover change in the study region. Under the increase of mixed forests within and below the basin, the basin-averaged precipitation and evaporation increased by 223.17 and 223.88 mm respectively, but the surface runoff decreased by 2.22 mm from 2006 to 2010. In other words, the forest-induced increase in evaporation exceeded that of precipitation along with decreased surface runoff. Importantly, the afforestation effects on water resources seemed to enhance with time, and the effects of the same vegetation change were different in dry and wet years with different precipitation amounts (i.e. different atmospheric circulation background). It should be noted that it is difficult to obtain one product that can explicitly reflect the spatial distribution of actual land cover change promoted by the Grain-for-Green project in the Yellow River basin, which is an important obstacle to clearly identify the reforestation impacts. A land cover dataset derived from advantages of multiple sets of data therefore needs to be proposed