The carbon footprint of food consumption in Beijing

Yan, 吴燕 Wu; Wang, Xiaoke; Fei, 逯非 Lu

doi:10.5846/stxb201101140074

Cited by 15 publications

(6 citation statements)

References 5 publications

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“…National health authorities that administer these surveys, like the U.S. Centers for Disease Control, could augment existing surveys or develop new ones to better track consumption of criteria foods (akin to criteria air pollutants) that have significant health and environmental impacts. Academics have developed one-off surveys that do this [57].…”

Section: More Accurately Measuring Consumptionmentioning

confidence: 99%

Do we accurately measure what we consume?

Goldstein,

Gounaridis,

Newell

et al. 2024

Environ. Res. Lett.

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Understanding how consumption patterns affect the environment and shape well-being hinges on the rationale that the data collected on what is consumed, who consumes it, and where it is consumed are indeed accurate. To identify these consumption patterns and recommend corresponding policies, researchers and policy makers often rely on national surveys. Studies have explored the accuracy of individual surveys and the level of agreement across surveys of the same type (e.g. household expenditures), but no studies have compared representative national surveys measuring consumption in different ways. This study compares household consumption measured as expenditures and as material consumption (i.e. physical units) to assess how well we currently measure what we consume. We use multiple rigorous, national surveys to estimate meat consumption, household energy use, and private automobile use in the United States, with consumption profiles parsed by affluence, race/ethnicity, and education. Our results indicate that commonly used surveys may not accurately track important aspects of household consumption. For meat consumption, which included 30 consumption profiles detailing the consumption patterns across different demographic characteristics and meat types (e.g. kilograms beef consumed/capita for Caucasians), there is considerable disagreement between data sources for 20 profiles. By contrast, national surveys accurately measure household energy and transport (disagreement for four profiles). Our findings indicate that national surveys more accurately measure consistently tracked, standardized consumables like electricity than irregularly tracked, variable goods such as food. These results cast doubt on studies that use national surveys to draw conclusions about the how the environmental impacts of food, and, potentially, other goods (e.g. manufactured goods) vary across demographic groups. Overcoming this challenge will necessitate new surveys, updating legacy databases, and harnessing breakthroughs in data science.

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Section: More Accurately Measuring Consumptionmentioning

confidence: 99%

Do we accurately measure what we consume?

Goldstein,

Gounaridis,

Newell

et al. 2024

Environ. Res. Lett.

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“…Since the majority of residents in Shanghai use natural gas for cooking, we will use natural gas for calculations. The average consumption of natural gas is approximately 0.4 m 3 /h [45]. During the food preparation stage, processing is required only for cooking, vegetable preparation, coffee, and tea.…”

Section: Food Preparation Stagementioning

confidence: 99%

Exploring Household Food Waste Reduction for Carbon Footprint Mitigation: A Case Study in Shanghai, China

Liu,

Shang,

Liu

2023

Foods

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With the steady growth of the global population and the accelerated urbanization process, the carbon footprint resulting from food waste has a significant impact on the environment and sustainable development. Considering Shanghai’s significance as a major urban center in China and a global hub for economic and cultural activities, this study primarily aims to accurately estimate household food waste generation and calculate the carbon footprint related to edible food waste. It analyzes the factors influencing household food waste generation and reviews the anti-food waste-related policies at both the national and Shanghai regional levels. The study reveals that although the Shanghai municipal government attaches great importance to the issue of food waste, the current policies mainly focus on the catering industry, and there is still a need for further strengthening measures to address food waste at the household level. In Shanghai, the per capita daily food waste generation is 0.57 kg, with 43.42% being edible food waste, contributing to a per capita daily carbon footprint of 1.17 kgCO2eq. Employing the logistic regression analysis to scrutinize the characteristics of the respondents, it is ascertained that education level and annual household income significantly influence food waste generation. In addition, excessive food quantities and expiration dates lead to high-frequency food waste. The culmination of this study is the formulation of a series of pragmatic and impactful policy recommendations aimed at curbing the carbon footprint that stems from food waste.

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“…GHG emissions from household consumption can be divided into three categories: GHG emissions from clothing, from food, and from household articles [52,53]. To avoid repeat calculations, housing and transportation can be included in energy activities, waste disposal, and other sectors.…”

Section: Ghg Emissions From Household Consumptionmentioning

confidence: 99%

Comparative Study on the Influencing Factors of the Greenhouse Gas Budget in Typical Cities: Case Studies of Beijing and Shenzhen

Yang

Huang

et al. 2023

Atmosphere

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Clarifying the pattern of the urban greenhouse gas (GHG) budget and its influencing factors is the basis of promoting urban low-carbon development. This paper takes Beijing and Shenzhen—the capital city and the most rapidly developing city in China, respectively—as case studies, comprehensively accounts their GHG budgets from 2005 to 2020, and investigates and compares the factors affecting their GHG budgets. The total GHG emissions in Beijing were lowest in 2005 (160.3 TgCO2 equivalents) and peaked at 227.7 TgCO2 equivalents in 2019, and then decreased to 209.1 TgCO2 equivalents in 2020. Meanwhile, the total GHG emissions in Shenzhen gradually increased from 36.0 TgCO2 equivalents in 2005 to 121.4 TgCO2 equivalents in 2019, and then decreased to 119.1 TgCO2 equivalents in 2020. The energy activity sector was the greatest contributor to GHG emissions in this period, accounting for 82.5% and 76.0% of the total GHG emissions in Beijing and Shenzhen, respectively. The carbon sink of the ecosystems of these two cities could absorb only small parts of their emissions, and the neutralization rates of sinks ranged from 1.7% to 2.3% in Beijing and from 0.3% to 1.5% in Shenzhen. The enhancement of population, economic product, and consumption increased the greenhouse gas emissions in both cities. A 1% increase in population size, per capita GD (gross domestic product), and residential consumption level would increase total GHG emissions by 0.181%, 0.019%, and 0.030% in Beijing, respectively. The corresponding increases in Shenzhen would be 0.180%, 0.243%, and 0.172%, respectively. The household size had opposite effects on the two cities, i.e., a 1% increase in household size would increase GHG emissions by 0.487% in Shenzhen but reduce them by 2.083% in Beijing. Each 1% increase in secondary industry and energy intensity would reduce GHG emissions by 0.553% and 0.110% in Shenzhen, respectively, which are more significant reductions than those in Beijing.

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The carbon footprint of food consumption in Beijing

Cited by 15 publications

References 5 publications

Do we accurately measure what we consume?

Do we accurately measure what we consume?

Exploring Household Food Waste Reduction for Carbon Footprint Mitigation: A Case Study in Shanghai, China

Comparative Study on the Influencing Factors of the Greenhouse Gas Budget in Typical Cities: Case Studies of Beijing and Shenzhen

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