35 research outputs found
Global and local carbon footprints of city of Hong Kong and Macao from 2000 to 2015
Hong Kong and Macao are featured with their urban metabolism as they heavily rely on the energy and resource supply from other regions. However, a comprehensive perspective is lacked to depict their CO2 emissions due to the independence of statistical data. Here we analyze the carbon footprints of Hong Kong and Macao. The direct energy-related emissions (Scope 1), the emissions of cross-boundary electricity (Scope 2), and the embodied emissions associated with trade (Scope 3) are examined. Scope 1 carbon footprints of the two areas were stabilized at 50 Mt, accounting for 0.6% of those from Mainland China in 2018. Their global footprints were approximately three times of their Scope 1 emissions, accompanied by a continuous growth between 2000 and 2015, and the contribution of their local footprints has doubled on average. Their Scope 3 emissions were mainly due to the enormous unfavorable balance of trade. Meanwhile, the increasing impact of imports' higher emission intensity on their Scope 3 emissions should not be ignored. We suggest that Hong Kong and Macao should adjust their mitigation policies that focus only on Scope 1 emissions as developed cities outsourcing production through supply chains
Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches
Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants.
However, current ground-level NO2 concentration data are lack of either
high-resolution coverage or full coverage national wide, due to the poor
quality of source data and the computing power of the models. To our knowledge,
this study is the first to estimate the ground-level NO2 concentration in China
with national coverage as well as relatively high spatiotemporal resolution
(0.25 degree; daily intervals) over the newest past 6 years (2013-2018). We
advanced a Random Forest model integrated K-means (RF-K) for the estimates with
multi-source parameters. Besides meteorological parameters, satellite
retrievals parameters, we also, for the first time, introduce socio-economic
parameters to assess the impact by human activities. The results show that: (1)
the RF-K model we developed shows better prediction performance than other
models, with cross-validation R2 = 0.64 (MAPE = 34.78%). (2) The annual average
concentration of NO2 in China showed a weak increasing trend . While in the
economic zones such as Beijing-Tianjin-Hebei region, Yangtze River Delta, and
Pearl River Delta, the NO2 concentration there even decreased or remained
unchanged, especially in spring. Our dataset has verified that pollutant
controlling targets have been achieved in these areas. With mapping daily
nationwide ground-level NO2 concentrations, this study provides timely data
with high quality for air quality management for China. We provide a universal
model framework to quickly generate a timely national atmospheric pollutants
concentration map with a high spatial-temporal resolution, based on improved
machine learning methods
COVID-19 causes record decline in global CO2 emissions
The considerable cessation of human activities during the COVID-19 pandemic
has affected global energy use and CO2 emissions. Here we show the
unprecedented decrease in global fossil CO2 emissions from January to April
2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when
compared with the period last year. In addition other emerging estimates of
COVID impacts based on monthly energy supply or estimated parameters, this
study contributes to another step that constructed the near-real-time daily CO2
emission inventories based on activity from power generation (for 29
countries), industry (for 73 countries), road transportation (for 406 cities),
aviation and maritime transportation and commercial and residential sectors
emissions (for 206 countries). The estimates distinguished the decline of CO2
due to COVID-19 from the daily, weekly and seasonal variations as well as the
holiday events. The COVID-related decreases in CO2 emissions in road
transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to
2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%),
residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2,
-15%). Regionally, decreases in China were the largest and earliest (234.5 Mt
CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S.
(162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional
nitrogen oxides concentrations observed by satellites and ground-based
networks, but the calculated signal of emissions decreases (about 1Gt CO2) will
have little impacts (less than 0.13ppm by April 30, 2020) on the overserved
global CO2 concertation. However, with observed fast CO2 recovery in China and
partial re-opening globally, our findings suggest the longer-term effects on
CO2 emissions are unknown and should be carefully monitored using multiple
measures
Carbon Monitor Cities, near-real-time daily estimates of CO2 emissions from 1500 cities worldwide
Building on near-real-time and spatially explicit estimates of daily carbon
dioxide (CO2) emissions, here we present and analyze a new city-level dataset
of fossil fuel and cement emissions. Carbon Monitor Cities provides daily,
city-level estimates of emissions from January 2019 through December 2021 for
1500 cities in 46 countries, and disaggregates five sectors: power generation,
residential (buildings), industry, ground transportation, and aviation. The
goal of this dataset is to improve the timeliness and temporal resolution of
city-level emission inventories and includes estimates for both functional
urban areas and city administrative areas that are consistent with global and
regional totals. Comparisons with other datasets (i.e. CEADs, MEIC, Vulcan, and
CDP) were performed, and we estimate the overall uncertainty to be 21.7%.
Carbon Monitor Cities is a near-real-time, city-level emission dataset that
includes cities around the world, including the first estimates for many cities
in low-income countries
Near-real-time monitoring of global COâ‚‚ emissions reveals the effects of the COVID-19 pandemic
The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO₂) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO₂ emissions (−1551 Mt CO₂) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially
Recommended from our members
Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic
The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially
Global patterns of daily CO2 emissions reductions in the first year of COVID-19
Day-to-day changes in CO2 emissions from human activities, in particular fossil-fuel combustion and cement production, reflect a complex balance of influences from seasonality, working days, weather and, most recently, the COVID-19 pandemic. Here, we provide a daily CO2 emissions dataset for the whole year of 2020, calculated from inventory and near-real-time activity data. We find a global reduction of 6.3% (2,232 MtCO2) in CO2 emissions compared with 2019. The drop in daily emissions during the first part of the year resulted from reduced global economic activity due to the pandemic lockdowns, including a large decrease in emissions from the transportation sector. However, daily CO2 emissions gradually recovered towards 2019 levels from late April with the partial reopening of economic activity. Subsequent waves of lockdowns in late 2020 continued to cause smaller CO2 reductions, primarily in western countries. The extraordinary fall in emissions during 2020 is similar in magnitude to the sustained annual emissions reductions necessary to limit global warming at 1.5°C. This underscores the magnitude and speed at which the energy transition needs to advance