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This paper describes a numerical experiment to test the ability of the proposed geoCARB satellite to estimate emissions of trace gases (CO2, CH4 and CO) in the polluted urban environment of Shanghai. The meteorology over Shanghai is simulated with the Weather Research and Forecasting (WRF) model for a 9-day period in August 2010. The meteorology includes water and ice clouds. The chemistry version of WRF (WRF-Chem V3.6.1) is used to predict the chemical composition, mass density and number density of aerosol species. Spectra in the bands measured by geo-CARB are calculated, including the effects of polarisation and multiple scattering of radiation by clouds, aerosols and molecules. Instrument noise is added, and column-averaged trace-gas mole fractions are estimated from the noisy spectra using an algorithm based on that for the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) but adapted to geoCARB. As expected, the high aerosol loadings are challenging. However, when the retrieval algorithm is provided with regionally adjusted aerosol optical properties, as might be determined from observations of dark targets within the field of regard, the accuracies of retrieved concentrations are comparable to those reported earlier for geoCARB. Statistics of the errors in the retrieved column-averaged concentrations are used to predict the reduction in uncertainty of surface emissions possible with remotely sensed data. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a carbon emission inventory in Shanghai for the period from 2000 to 2008 covering six sectors of stationary combustion, transportation, industrial processes, waste disposal and treatment, agricultural activities and forestry sink and three greenhouse gases (CO2, CH4, and N2O). The aim is to reflect carbon emissions in Shanghai, and guides policymakers to take effective actions to mitigate carbon emissions. Several results are obtained: (1) the total carbon emissions in Shanghai increased by 48%, from 136TgCO2e in 2000 to 200TgCO2e in 2008; (2) only the sector of agriculture activities saw reduced emissions; (3) the comparisons among Shanghai, China and world average level confirm that during 2000–2008 Shanghai''s carbon emissions per capita are higher than both the world and the China average level, and its carbon emission per GDP is also higher than the world average level, but both of them are lower than the China average level; (4) in 2008, Shanghai''s carbon emission per GDP is around 10tons CO2 per $10,000 and higher than that of Taiwan, Hong Kong, the G7 and the BRIC (Brazil, Russia, India and China) except China and India. In addition, this paper also illustrates the problems about China statistical system in terms of emission inventory establishment, including the classification system, data quality and temporal resolution. [Copyright &y& Elsevier]

In recent years, as China's peaking carbon dioxide emissions and air pollution control projects have converged, scholars have begun to focus on the synergistic mechanisms of greenhouse gas and pollution gas reduction. In 2020, the unprecedented coronavirus pandemic, which led to severe nationwide blockade measures, unexpectedly provided a valuable opportunity to study the synergistic reduction in greenhouse gases and polluting gases. This paper uses a combination of NO2, O3, and CO2 column concentration products from different satellites and surface concentrations from ground-based stations to investigate potential correlations between these monitoring indicators in four Chinese representative cities. We found that XCO2 decreased in March to varying degrees in different cities. It was witnessed that the largest decrease in CO2, −1.12 ppm, occurred in Wuhan, i.e., the first epicenter of COVID-19. We also analyzed the effects of NO2 and O3 concentrations on changes in XCO2. First, in 2020, we used a top-down approach to obtain the conclusion that the change amplitude of NO2 concentration in Beijing, Shanghai, Guangzhou, and Wuhan were −24%, −18%, −4%, and −39%, respectively. Furthermore, the O3 concentration increments were 5%, 14%, 12%, and 14%. Second, we used a bottom-up approach to obtain the conclusion that the monthly averaged NO2 concentrations in Beijing, Shanghai, and Wuhan in March had the largest changes, changing to −39%, −40%, and −61%, respectively. The corresponding amounts of changes in monthly averaged O3 concentrations were −14%, −2%, and 9%. However, the largest amount of change in monthly averaged NO2 concentration in Guangzhou was found in December 2020, with a value of −40%. The change in O3 concentration was −12% in December. Finally, we analyzed the relationship of NO2 and O3 concentrations with XCO2. Moreover, the results show that the effect of NO2 concentration on XCO2 is positively correlated from the point of the satellite (R = 0.4912) and the point of the ground monitoring stations (R = 0.3928). Surprisingly, we found a positive (in satellite observations and R = 0.2391) and negative correlation (in ground monitoring stations and R = 0.3333) between XCO2 and the O3 concentrations. During the epidemic period, some scholars based on model analysis found that Wuhan's carbon emissions decreased by 16.2% on average. Combined with satellite data, we estimate that Wuhan's XCO2 fell by about 1.12 ppm in February. At last, the government should consider reducing XCO2 and NO2 concentration at the same time to make a synergistic reduction. [ABSTRACT FROM AUTHOR]

With the rapid development of global industrialization and modernization, carbon emissions have brought about serious climate warming and environmental pollution problems. Chinese enterprises, as the major players in carbon emissions, are important in terms of promoting the green transformation of the economy. It is particularly important to investigate the relationship and mechanism of action between carbon emission reduction and corporate sustainable development in Chinese enterprises. This study aims to determine whether reducing the intensity of carbon emissions can make businesses more sustainable and to analyze the moderating influences of government environmental subsidies, media monitoring, and executives' green opinions on the link between the two variables. The study sample consists of Shanghai and Shenzhen A-shares data from 2015 to 2020, and a fixed-effects model is employed for analysis. Data were obtained from the China Stock Market & Accounting Research database, the Financial News Database of Listed Companies, and enterprise financial statement notes, etc. Stata17.0 was used to clean and analyze the data. The results indicate that businesses can greatly improve their long-term viability by lowering their carbon emissions. Additionally, government environmental subsidies, media monitoring, and executives' green perceptions all enhance the correlation between corporate sustainability and reduce carbon emission intensity. This study not only enriches the relationship between environmental governance and sustainable development from a theoretical perspective, but also further expands the stakeholder theory. It also finds the mechanism of the role of the government and media on corporate carbon emissions for sustainable development in practice, which provides effective guidance to accelerate the promotion of carbon emission reduction and, thus, the sustainable development of Chinese enterprises. [ABSTRACT FROM AUTHOR]