

世界地理研究 ›› 2026, Vol. 35 ›› Issue (5): 157-170.DOI: 10.3969/j.issn.1004-9479.2026.05.20240736
• 文化与社会 • 上一篇
收稿日期:2024-09-04
修回日期:2025-03-11
出版日期:2026-05-15
发布日期:2026-05-27
通讯作者:
郑家怡
作者简介:龚利(1981—),男,副研究员,博士,研究方向为能源地理与区域发展,E-mail: lgong@re.ecnu.edu.cn。
基金资助:
Li GONG1,2(
), Jiayi ZHENG1,2(
), Lu MA1,2
Received:2024-09-04
Revised:2025-03-11
Online:2026-05-15
Published:2026-05-27
Contact:
Jiayi ZHENG
摘要:
随着生活能源消费规模的扩大,居民生活能源消费已成为推进能源转型和节能降碳的关键领域。本研究以城乡居民生活能源消费为研究对象,揭示2007—2020年中国城乡生活能源消费变化特征,并结合LMDI模型和STIRPAT模型,分别探讨城镇和乡村生活能源消费的影响因素及其作用效应。结果表明:①研究期内中国城乡居民生活能源消费量总体呈现波动上升趋势。其中,城镇生活能源消费量占全国总量的比重持续高于乡村。②城乡生活能源消费结构呈现多元化、清洁化趋势。其中,乡村天然气、热力和电力的消费比重增长率均高于城镇,但城乡天然气消费占比均较低。③影响因素方面,人口规模、能源强度、经济发展、产业结构、粗放消费与清洁消费均在不同程度上对城镇和乡村生活能源消费产生了影响,且具有显著差异。分区域来看,中部和东部的城镇以及中部和东北部的乡村更易受到人口规模、能源强度、经济发展等因素的影响。未来推进节能降碳工作,可以考虑增强城镇居民节能意识,加快建设乡村电网、天然气设备等基础设施,进一步提高天然气消费比重,推进技术进步和优化乡村电力生产结构。
龚利, 郑家怡, 马璐. 中国城乡居民生活能源消费特征及影响因素研究[J]. 世界地理研究, 2026, 35(5): 157-170.
Li GONG, Jiayi ZHENG, Lu MA. Research on the characteristics and influencing factors of domestic energy consumption by urban and rural residents in China[J]. World Regional Studies, 2026, 35(5): 157-170.
| 年份 | 城镇 | ||||
|---|---|---|---|---|---|
| △P | △I | △A | △E | △N | |
| 2007—2008 | 419.38 | -31.61 | 1 649.99 | -2.64 | -3 113.92 |
| 2008—2009 | 395.68 | 63.53 | 1 061.02 | 14.53 | 1 932.04 |
| 2009—2010 | 748.11 | -307.18 | 2 518.28 | 1.28 | -199.75 |
| 2010—2011 | 689.82 | -291.86 | 2 886.28 | 0.04 | -1 576.08 |
| 2011—2012 | 640.70 | -300.43 | 1 696.71 | 1.74 | -1.82 |
| 2012—2013 | 647.98 | 40.35 | 1 122.20 | -4.30 | -3 641.51 |
| 2013—2014 | 596.95 | -3.78 | 1 125.63 | 0.45 | -385.12 |
| 2014—2015 | 708.92 | -418.39 | 906.47 | 0.27 | 355.51 |
| 2015—2016 | 741.17 | -305.05 | 1 367.19 | 0.15 | -821.24 |
| 2016—2017 | 706.29 | -260.11 | 1 775.37 | 0.62 | -234.14 |
| 2017—2018 | 642.75 | -261.07 | 1 697.00 | 1.37 | -271.96 |
| 2018—2019 | 638.22 | -288.01 | 1 674.06 | 0.23 | -1 111.44 |
| 2019—2020 | 578.11 | -162.93 | 188.11 | 0.59 | 625.87 |
| 年份 | 乡村 | ||||
| △P | △I | △A | △E | △N | |
| 2007—2008 | -135.23 | 7.09 | 1 525.29 | 11.03 | -531.28 |
| 2008—2009 | -117.66 | 1.73 | 493.22 | -1.20 | -477.25 |
| 2009—2010 | -288.23 | -17.67 | 1 592.13 | 0.40 | -588.57 |
| 2010—2011 | -195.28 | -72.30 | 1 858.62 | 2.28 | -393.80 |
| 2011—2012 | -210.77 | -163.83 | 1 454.13 | 0.67 | -638.08 |
| 2012—2013 | -273.92 | -76.06 | 1 293.70 | 0.16 | -758.70 |
| 2013—2014 | -248.58 | -147.05 | 1 026.14 | 0.06 | -248.69 |
| 2014—2015 | -382.46 | -124.96 | 1 049.43 | 0.10 | 315.92 |
| 2015—2016 | -378.51 | -229.73 | 1 216.20 | 0.58 | -84.55 |
| 2016—2017 | -394.39 | -241.80 | 363.10 | 0.83 | 1 149.42 |
| 2017—2018 | -407.77 | -203.50 | 1 237.50 | 1.40 | 26.29 |
| 2018—2019 | -420.21 | -145.10 | 1 810.91 | -0.03 | -1 287.32 |
| 2019—2020 | -462.45 | -1 867.72 | 3 786.30 | 0.41 | -712.89 |
表1 主要年份中国城乡生活能源消费驱动效应演变
Tab. 1 Evolution of driving effect of energy consumption in urban and rural China in major years
| 年份 | 城镇 | ||||
|---|---|---|---|---|---|
| △P | △I | △A | △E | △N | |
| 2007—2008 | 419.38 | -31.61 | 1 649.99 | -2.64 | -3 113.92 |
| 2008—2009 | 395.68 | 63.53 | 1 061.02 | 14.53 | 1 932.04 |
| 2009—2010 | 748.11 | -307.18 | 2 518.28 | 1.28 | -199.75 |
| 2010—2011 | 689.82 | -291.86 | 2 886.28 | 0.04 | -1 576.08 |
| 2011—2012 | 640.70 | -300.43 | 1 696.71 | 1.74 | -1.82 |
| 2012—2013 | 647.98 | 40.35 | 1 122.20 | -4.30 | -3 641.51 |
| 2013—2014 | 596.95 | -3.78 | 1 125.63 | 0.45 | -385.12 |
| 2014—2015 | 708.92 | -418.39 | 906.47 | 0.27 | 355.51 |
| 2015—2016 | 741.17 | -305.05 | 1 367.19 | 0.15 | -821.24 |
| 2016—2017 | 706.29 | -260.11 | 1 775.37 | 0.62 | -234.14 |
| 2017—2018 | 642.75 | -261.07 | 1 697.00 | 1.37 | -271.96 |
| 2018—2019 | 638.22 | -288.01 | 1 674.06 | 0.23 | -1 111.44 |
| 2019—2020 | 578.11 | -162.93 | 188.11 | 0.59 | 625.87 |
| 年份 | 乡村 | ||||
| △P | △I | △A | △E | △N | |
| 2007—2008 | -135.23 | 7.09 | 1 525.29 | 11.03 | -531.28 |
| 2008—2009 | -117.66 | 1.73 | 493.22 | -1.20 | -477.25 |
| 2009—2010 | -288.23 | -17.67 | 1 592.13 | 0.40 | -588.57 |
| 2010—2011 | -195.28 | -72.30 | 1 858.62 | 2.28 | -393.80 |
| 2011—2012 | -210.77 | -163.83 | 1 454.13 | 0.67 | -638.08 |
| 2012—2013 | -273.92 | -76.06 | 1 293.70 | 0.16 | -758.70 |
| 2013—2014 | -248.58 | -147.05 | 1 026.14 | 0.06 | -248.69 |
| 2014—2015 | -382.46 | -124.96 | 1 049.43 | 0.10 | 315.92 |
| 2015—2016 | -378.51 | -229.73 | 1 216.20 | 0.58 | -84.55 |
| 2016—2017 | -394.39 | -241.80 | 363.10 | 0.83 | 1 149.42 |
| 2017—2018 | -407.77 | -203.50 | 1 237.50 | 1.40 | 26.29 |
| 2018—2019 | -420.21 | -145.10 | 1 810.91 | -0.03 | -1 287.32 |
| 2019—2020 | -462.45 | -1 867.72 | 3 786.30 | 0.41 | -712.89 |
| 变量 | (1) | (2) | (3) | (4) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 乡村 | 城镇 | 城镇 | 乡村 | |||||||
| 东部 | 中部 | 西部 | 东北部 | 东部 | 中部 | 西部 | 东北部 | |||
| lnP | 0.52*** | 0.65*** | 1.11*** | 1.40*** | 0.65*** | 0.52*** | 0.42*** | 0.91*** | 0.82*** | 0.836*** |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| lnN | 0.95*** | 0.07* | 0.12*** | 0.41*** | 1.06*** | 0.54*** | 1.03*** | 0.87*** | 0.83*** | 0.606*** |
| (0.00) | (0.08) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| lnA | 0.13*** | 0.17*** | 1.24*** | 0.04** | 0.11 | 0.42** | 0.55** | 0.41*** | 0.10*** | 0.876*** |
| (0.00) | (0.00) | (0.00) | (0.01) | (0.29) | (0.04) | (0.03) | (0.00) | (0.00) | (0.00) | |
| lnI | -0.00 | 0.12*** | 0.44*** | 0.13 | -0.01 | 0.07** | 0.11*** | 0.56*** | 0.21* | 0.319* |
| (0.87) | (0.00) | (0.00) | (0.35) | (0.86) | (0.01) | (0.00) | (0.00) | (0.07) | (0.07) | |
| lnE1 | -0.01 | 0.30*** | 0.11*** | 0.17*** | -0.06** | 0.08 | 0.01 | 0.04 | -0.08* | 0.178*** |
| (0.83) | (0.00) | (0.00) | (0.00) | (0.02) | (0.20) | (0.74) | (0.13) | (0.07) | (0.00) | |
| lnE2 | 0.11*** | -0.18*** | -0.12*** | -0.37*** | 0.00 | -0.09 | 0.10*** | -0.01 | -0.09*** | -0.027 |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.93) | (0.61) | (0.00) | (0.28) | (0.00) | (0.69) | |
| 截距项 | 1.75*** | 0.59*** | 1.24** | -1.78*** | 3.07*** | 3.66*** | 2.19*** | 2.45*** | 1.48*** | 2.012*** |
| (0.00) | (0.00) | (0.02) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| R2 | 0.89 | 0.70 | 0.94 | 0.92 | 0.86 | 0.96 | 0.63 | 0.59 | 0.55 | 0.837 |
表2 中国城乡生活能源消费基准回归结果
Tab. 2 Regression results of China's urban and rural domestic energy consumption benchmark
| 变量 | (1) | (2) | (3) | (4) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 乡村 | 城镇 | 城镇 | 乡村 | |||||||
| 东部 | 中部 | 西部 | 东北部 | 东部 | 中部 | 西部 | 东北部 | |||
| lnP | 0.52*** | 0.65*** | 1.11*** | 1.40*** | 0.65*** | 0.52*** | 0.42*** | 0.91*** | 0.82*** | 0.836*** |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| lnN | 0.95*** | 0.07* | 0.12*** | 0.41*** | 1.06*** | 0.54*** | 1.03*** | 0.87*** | 0.83*** | 0.606*** |
| (0.00) | (0.08) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| lnA | 0.13*** | 0.17*** | 1.24*** | 0.04** | 0.11 | 0.42** | 0.55** | 0.41*** | 0.10*** | 0.876*** |
| (0.00) | (0.00) | (0.00) | (0.01) | (0.29) | (0.04) | (0.03) | (0.00) | (0.00) | (0.00) | |
| lnI | -0.00 | 0.12*** | 0.44*** | 0.13 | -0.01 | 0.07** | 0.11*** | 0.56*** | 0.21* | 0.319* |
| (0.87) | (0.00) | (0.00) | (0.35) | (0.86) | (0.01) | (0.00) | (0.00) | (0.07) | (0.07) | |
| lnE1 | -0.01 | 0.30*** | 0.11*** | 0.17*** | -0.06** | 0.08 | 0.01 | 0.04 | -0.08* | 0.178*** |
| (0.83) | (0.00) | (0.00) | (0.00) | (0.02) | (0.20) | (0.74) | (0.13) | (0.07) | (0.00) | |
| lnE2 | 0.11*** | -0.18*** | -0.12*** | -0.37*** | 0.00 | -0.09 | 0.10*** | -0.01 | -0.09*** | -0.027 |
| (0.00) | (0.00) | (0.00) | (0.00) | (0.93) | (0.61) | (0.00) | (0.28) | (0.00) | (0.69) | |
| 截距项 | 1.75*** | 0.59*** | 1.24** | -1.78*** | 3.07*** | 3.66*** | 2.19*** | 2.45*** | 1.48*** | 2.012*** |
| (0.00) | (0.00) | (0.02) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
| R2 | 0.89 | 0.70 | 0.94 | 0.92 | 0.86 | 0.96 | 0.63 | 0.59 | 0.55 | 0.837 |
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